system

Abstract

Provide a system. A method for storing documents uploaded from a terminal; a means for extracting important information from the stored documents; A means for automatically generating a document template by referencing a past database based on the extracted information; A means for users to review and edit the automatically generated documents; A means of automatically notifying the relevant departments of the final document; A system including:

Description

[Technical Field]

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

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Creating traditional sales documents and notification documents requires a lot of manual work, which is time-consuming and labor-intensive, and prone to errors. Furthermore, when creating new documents by referencing similar documents from the past, selecting the appropriate template and updating the information is cumbersome, making it difficult to do this efficiently. In this situation, it is difficult to quickly and accurately create and update documents and notify relevant departments. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for saving documents uploaded from a terminal, a means for extracting important information from the saved documents, a means for automatically generating document templates by referencing a past database based on the extracted information, a means for users to review and edit the automatically generated documents, and a means for automatically notifying relevant departments of the final documents. This system enables efficient document creation and updating, reduces errors, and enables prompt and accurate notification. Furthermore, by including a means for selecting templates similar to information extracted from a past database and a means for extracting important information from documents using natural language processing technology, even greater accuracy and efficiency are achieved.

[0006] A "terminal" is an electronic device such as a computer or smartphone that is operated by a user and used to upload documents.

[0007] "Upload" refers to the operation of sending a file from a terminal to a server and saving it.

[0008] "Documents" are electronic documents created and edited by users, such as CP materials and service proposal materials.

[0009] "Saving" is an operation for holding an uploaded document on a server and storing it for necessary processing.

[0010] The term "means" refers to a specific method, device, or program for realizing the present invention.

[0011] "Key information" refers to the key data contained within the document, such as features, pricing, target market, etc., required for the present invention.

[0012] "Extraction" refers to the process of extracting necessary information from a stored document.

[0013] The "historical database" is a collection of information in which previous development documents and templates are stored.

[0014] A "document template" is a format that serves as a model when creating a document, and is a framework for embedding necessary information.

[0015] "Automatic generation" refers to the process by which a program creates a document template based on required information without manual intervention.

[0016] "Means for users to view and edit" refers to a function that displays the automatically generated document and provides an interface that allows users to view and modify its contents.

[0017] "Relevant departments" are those to whom the final document will be notified, such as the legal department or digital marketing department.

[0018] "Notification" refers to the operation of informing the relevant parties of the contents of a document after it has been completed.

[0019] "Natural language processing technology" is a technology that allows computers to analyze human language and understand and process its meaning. [Brief explanation of the drawings]

[0020] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7]FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0021] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0022] First, the terms used in the following description will be explained.

[0023] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0024] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0025] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0026] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0027] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0031] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0032] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0033] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0034] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0035] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0038] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0039] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0040] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0041] The present invention relates to a system that enables users to upload various sales-related documents from their terminals and a server to analyze and process the documents, thereby achieving efficient document creation and notification. The following describes in detail an embodiment of the present invention.

[0042] Upload method

[0043] First, a user selects a document file (e.g., a CP document or a service proposal document) using a terminal and uploads it to the server. The uploaded document is saved on the server, and metadata such as the file name, user ID, and upload date and time are recorded along with it.

[0044] Information extraction method

[0045] The server analyzes the stored documents and uses natural language processing techniques to extract key information, such as product name, features, pricing, target market, etc.

[0046] Automated document generation methods

[0047] Next, the server selects an appropriate document template based on the extracted important information by referencing the historical database, and automatically generates a new document by embedding the extracted information into the template.

[0048] User review and editing options

[0049] The generated document can be viewed by the user on their device, and they can edit the content as needed. The editing interface is designed for ease of use.

[0050] Document notification method

[0051] The server automatically notifies the relevant departments of the final edited document via email or chat, allowing departments such as the legal department and digital marketing department to instantly view the new document contents.

[0052] Specific examples

[0053] For example, suppose User A uploads a service proposal document for a new product from their device. The server uses natural language processing technology to extract product features and pricing information from the document. Based on the extracted information, the server references proposal document templates from past similar products and automatically generates a new proposal document. User A reviews the generated document on their device and makes any necessary corrections, after which the server automatically notifies the legal department and digital marketing department of the final version.

[0054] In this way, the present invention provides a system that significantly improves the efficiency of document creation, reduces the occurrence of errors, and enables rapid information sharing.

[0055] The processing flow will be explained below.

[0056] Step 1:

[0057] The user selects a document file using the terminal and clicks the upload button. The terminal sends the selected file to the server.

[0058] Step 2:

[0059] The server receives the uploaded document file and saves it in storage. At the same time, the server records metadata such as the file name, user ID, and upload date and time in a database.

[0060] Step 3:

[0061] The server analyzes the stored document files and uses natural language processing (NLP) techniques to extract important information from within the documents (e.g., product name, features, pricing, target market).

[0062] Step 4:

[0063] Based on the extracted key information, the server searches for and selects the most similar document template by referring to a database of past development documents and templates.

[0064] Step 5:

[0065] The server then processes the selected template to embed the extracted important information, resulting in a new, automatically generated document.

[0066] Step 6:

[0067] The server sends the automatically generated document to the user's device, allowing the user to check the document contents. The user can then check the document on their device and edit it as necessary.

[0068] Step 7:

[0069] The user edits the document and sends it to the server, which receives the edits and saves them as the final document.

[0070] Step 8:

[0071] The server automatically notifies the relevant departments (e.g., legal department, digital marketing department) of the final document via email or chat system, allowing the relevant parties to instantly check the document contents.

[0072] Example 1

[0073] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0074] In conventional document creation systems, the processes of document uploading, analysis, generation, editing, and notification are fragmented, resulting in low overall efficiency and delays in information sharing. Furthermore, systems that automate document creation by applying natural language processing and generative AI models are not yet widespread, resulting in a heavy burden on human resources. The present invention aims to solve these issues and significantly improve the efficiency of document creation and notification.

[0075] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0076] In this invention, the server includes means for saving documents uploaded from a terminal, means for extracting important information from the saved documents using natural language processing technology, means for automatically generating a document template based on the extracted information and referring to a past database, means for generating a document based on the extracted information using a generative AI model, means for allowing a user to check and edit the automatically generated document, means for automatically notifying relevant departments of the final document, and means for recording metadata of the saved document. This automates the entire process from document creation to notification, improving overall efficiency and enabling fast and accurate information sharing.

[0077] A "terminal" is an electronic device such as a computer or smartphone that is operated by a user.

[0078] A "server" is a computer system that receives data sent from a terminal via a network and performs various functions such as storage, analysis, processing, and notification.

[0079] A "document" is a collection of information stored in electronic file format, and includes sales-related materials, proposals, and the like.

[0080] "Saving" is the process of storing a document uploaded to a server in storage so that it can be accessed later.

[0081] "Metadata" is additional information associated with a document, including file name, user ID, upload date and time, etc.

[0082] "Natural language processing technology" is a technology that allows computers to understand human language and is used to extract important information from documents.

[0083] "Important Information" is information necessary to understand the significance of the document, such as the product name, features, pricing, target market, etc., contained within the document.

[0084] A "database" is a system that stores multiple data in an organized manner and allows them to be searched and accessed efficiently.

[0085] A "document template" is a model of a document with a standard format and structure, and serves as the basis for creating a new document.

[0086] A "generative AI model" is an artificial intelligence model that uses machine learning and deep learning to automatically generate new documents.

[0087] "Validation" is the process in which a user checks the content of a generated document and considers its accuracy and suitability.

[0088] "Editing" is the process by which a user changes or modifies the content of a generated document.

[0089] "Notification" is the process of informing relevant departments of the final completed document, and is mainly done via email or chat systems.

[0090] "Related departments" are departments responsible for work related to the generated documents, such as the legal department and the digital marketing department.

[0091] MODE FOR CARRYING OUT THE INVENTION

[0092] The present invention relates to a system that enables efficient document creation and notification by allowing users to upload sales-related documents from their terminals and having a server analyze and process the documents. The following describes in detail an embodiment of the present invention.

[0093] Upload method

[0094] First, the user uses the terminal to select a current sales-related document (e.g., CP document or service proposal document) and upload it to the server. In this upload process, the user opens a file selection dialog on the terminal screen and selects the desired document file. Once the document file is selected, the user clicks the "Upload" button to send the document to the server.

[0095] Preservation and metadata recording methods

[0096] The server receives the document file sent from the device and saves the document in a specific directory. At the same time, it records metadata such as the file name, user ID, and upload date and time in a database (e.g., an SQL database). In this step, the server uses an appropriate SQL query to insert the metadata into the database, allowing the document to be easily searched and referenced later.

[0097] Means of Information Extraction

[0098] The server analyzes the stored documents using natural language processing (NLP) technology (e.g., TENSORFLOW®, SpaCy) to extract important information. This important information includes product names, features, pricing, target markets, etc. Specifically, the NLP engine tokenizes the documents and analyzes the meaning of each token. The analysis results are stored in a database as structured data.

[0099] Means of automatic document generation

[0100] Next, the server selects an appropriate document template based on the extracted key information by referencing a historical database (e.g., MongoDB or SQL database). Once a template is selected, the server provides the information to a generative AI model (e.g., OpenAI's GPT-4) to automatically generate a new document. Specifically, the server embeds the information into the template and outputs it as the final document format.

[0101] User review and editing means

[0102] The generated document is displayed on the user's device, where the user can review the content and make edits as necessary. The user can directly modify each field of the document through the web browser interface. After completing the modifications, the user clicks the "Save" button to send the changes to the server.

[0103] Final Document Notification Method

[0104] Once the user has finished editing the document, it is saved back to the server. The server then automatically notifies the relevant departments of the final version of the document. This notification is done by sending email using the SMTP protocol or by sending a chat message using the Slack API. Specifically, the server obtains the notification address and sends an email or chat message.

[0105] Specific examples

[0106] For example, suppose User A uploads a service proposal document for a new product from their device. The server receives the document and uses natural language processing technology to extract product features and pricing information. Based on the extracted information, the server references past proposal document templates for similar products and generates a new proposal document. User A then reviews the generated document on their device and makes any necessary corrections. Finally, the server notifies the legal department and digital marketing department of the completed document.

[0107] Prompt Sentence Examples

[0108] "Generate a service proposal for a new product. Create the proposal using the following information:

[0109] Product Name: Product X

[0110] Features: high speed processing, low power consumption

[0111] Price: 50,000 yen

[0112] Target market: Small and medium-sized businesses

[0113] Please embed this information in your pitch deck template."

[0114] Thus, the present invention automates each step of the document creation process, greatly improving efficiency.

[0115] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0116] Step 1:

[0117] The user selects a document file (e.g., CP materials or service proposal materials) using the terminal and clicks the "Upload" button. This sends the document file selected through the file selection dialog to the server.

[0118] Input: A document file selected by the user

[0119] Output: The document file sent to the server

[0120] Step 2:

[0121] The server saves the received document file in a specific directory. It also records metadata such as the file name, user ID, and upload date and time in a database. For this purpose, it uses an SQL database to store the metadata. The server receives an HTTP POST request and processes the document file and metadata included in the request.

[0122] Input: Document file sent from the device, metadata (file name, user ID, upload date and time)

[0123] Output: Saved document files, metadata recorded in a database

[0124] Step 3:

[0125] The server analyzes the stored documents using natural language processing techniques (e.g., TensorFlow, SpaCy) to extract important information. The server tokenizes the document text and extracts information based on specific patterns or keywords.

[0126] Input: Saved document file

[0127] Output: Extracted key information (product name, features, pricing, target market)

[0128] Step 4:

[0129] Based on the extracted information, the server selects an appropriate document template by referencing a historical database (e.g., MongoDB, SQL database). The server executes a database query to search and retrieve similar historical document templates.

[0130] Input: Extracted important information

[0131] Output: Selected document template

[0132] Step 5:

[0133] The server uses a generative AI model (e.g., OpenAI's GPT-4) to automatically generate new documents. Specifically, it inputs the extracted information as prompts into the generative AI model and embeds the generated document text into a template.

[0134] Input: Selected document template, extracted key information

[0135] Output: Auto-generated document

[0136] Step 6:

[0137] The generated document is displayed on the user's device, where the user can review the content and edit it as necessary. The user can also directly modify the document text through the web browser interface.

[0138] Input: Auto-generated document

[0139] Output: The corrected document

[0140] Step 7:

[0141] Once the user has completed the revisions, the document is saved back to the server, which then automatically notifies the relevant departments of the final version of the document and sends an email or chat message using an SMTP server or Slack API.

[0142] Input: revised document, contact information of relevant departments

[0143] Output: Final document notified to relevant departments

[0144] This series of processes automates and efficiently executes the process from when a user uploads a document to when the server analyzes, generates, and notifies the user.

[0145] (Application example 1)

[0146] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0147] In today's logistics centers, the creation and management of a wide variety of business-related documents is required. However, manual document creation is time-consuming and carries a high risk of errors. Furthermore, delayed sharing of information reduces operational efficiency. There is a need for a method to solve these problems and achieve efficient and accurate document creation and rapid information sharing.

[0148] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0149] In this invention, the server includes means for saving documents uploaded from terminals, means for extracting important information from the saved documents, means for automatically generating document templates by referencing a past database based on the extracted information, means for allowing users to check and edit the automatically generated documents, means for automatically notifying relevant departments of the final documents, means for extracting important logistics information (product name, quantity, date of receipt, etc.) from the documents and automatically generating an appropriate inventory report template if the documents include business-related documents used in the logistics center, and means for allowing users to check and edit the documents generated on their smart devices. This improves the efficiency of business document creation in logistics centers, reduces errors, and enables rapid information sharing.

[0150] A "terminal" is an electronic device such as a computer or smartphone used by a user.

[0151] A "document" is a digital file that consists of text, images, etc.

[0152] "Saving" refers to the act of recording an uploaded document in a storage device within the server.

[0153] "Extraction" is the act of analyzing and extracting important information from within a document.

[0154] "Natural language processing technology" is a technology that allows computers to analyze and understand natural language.

[0155] A "database" is a collection of documents and information that have been stored in the past.

[0156] A "document template" is a pattern that defines the format and structure of a document.

[0157] "Automatic generation" refers to the act of a computer creating a document based on extracted information.

[0158] "Verification" is the act of a user reviewing the generated document.

[0159] "Editing" is an action in which a user modifies the content of a generated document.

[0160] "Notification" is the act of communicating to report the generated document to the relevant department.

[0161] A "logistics center" is a facility that handles logistics operations such as receiving, storing, and shipping goods.

[0162] "Business-related documents" are documents necessary for carrying out daily business.

[0163] A "smart device" is a mobile information terminal with advanced functions, such as a smartphone or tablet.

[0164] An "inventory report" is a document used to record inventory status.

[0165] In the system realizing the present invention, the following elements are used to automatically generate and notify documents.

[0166] Hardware and software used

[0167] 1. Hardware:

[0168] Smart devices (smartphones and tablets)

[0169] server

[0170] 2. Software:

[0171] Python

[0172] Django (server-side framework)

[0173] NLTK (Natural Language Processing Library)

[0174] React Native (application development for smart devices)

[0175] Data processing and calculation

[0176] Upload method

[0177] Users use their smart devices to select business-related documents (e.g., inventory lists and outbound lists) and upload them to the server. The React Native application makes it easy to select and upload files.

[0178] Preservation methods

[0179] Uploaded documents are stored in a database on the server using the Django framework, along with metadata such as file name, user ID, and upload date and time.

[0180] Information extraction method

[0181] The stored documents are analyzed on the server using Python and NLTK, and key logistics information such as product name, quantity, and receipt date is extracted from the documents using natural language processing technology.

[0182] Automated document generation methods

[0183] Based on the extracted information, the server selects an appropriate inventory report template from the historical database, and by filling in the extracted information in the template, a new business document is automatically generated.

[0184] User review and editing options

[0185] The generated documentation is made available for users to view on their smart devices, and users can edit the generated documentation using a React Native application.

[0186] Document notification method

[0187] The server automatically notifies the relevant departments of the final edited version via email or chat system (e.g., Slack), allowing warehouse managers and transportation staff to instantly check the contents of the new document.

[0188] Specific examples

[0189] As an example, consider the case where User B at a logistics center uploads a list of products received that day. The server uses natural language processing technology to extract important information from the list, such as product name, quantity, and receiving date. Next, it automatically generates a new report by filling in an appropriate inventory report template based on the extracted information. User B checks the generated report using a smart device and makes any necessary corrections. The server then automatically notifies the warehouse manager and transportation department staff of the corrected report.

[0190] Prompt Sentence Examples

[0191] "Develop a program to automatically generate inventory reports for a distribution center. Follow these steps:

[0192] 1. Upload business-related documents (stock receipt lists and stock issue lists) from your smart device.

[0193] 2. Extract key information from documents, such as product name, quantity, and receipt date, using natural language processing.

[0194] 3. Based on the extracted information, select an appropriate inventory report template and automatically generate a new document.

[0195] 4. Allow users to view and edit the generated documents on their smart devices.

[0196] 5. Notify the warehouse manager and transportation department staff of the edited document.

[0197] This invention improves the efficiency of business document creation at logistics centers, reduces errors, and enables quick information sharing.

[0198] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0199] Step 1:

[0200] A user uses a smart device to select business-related documents (e.g., inventory receipt list or inventory issue list) and upload them to the server. The input is the document file, and the output is the transfer of the document file to the server. The selection and uploading are performed through a React Native application on the smart device.

[0201] Step 2:

[0202] The server uses the Django framework to store the uploaded document in a database. The input is the uploaded document file and its metadata (file name, user ID, upload date and time, etc.), and the output is a record of the document and its metadata in the database. Specifically, the server stores the document data and its metadata in the database.

[0203] Step 3:

[0204] The server analyzes the stored documents using natural language processing technology and extracts important logistics information (product name, quantity, date of receipt, etc.). The input is the document file stored in the database, and the output is the extracted important information. Specifically, the server uses Python and NLTK to analyze the documents and extract the specified information.

[0205] Step 4:

[0206] The server selects an appropriate inventory report template based on the information extracted from the historical database and automatically generates a new business document. The input is the extracted important information and the template database, and the output is the newly generated business document. Specifically, the server embeds the extracted information into the template to create a new document.

[0207] Step 5:

[0208] The server sends the generated business document to the smart device for the user to review and edit. The input is the generated document, and the output is the document modified by the user. Specifically, the user uses a React Native application on the smart device to review the generated document and make any necessary edits.

[0209] Step 6:

[0210] The server automatically notifies the relevant departments of the final version of the document. The input is the final version of the document modified by the user, and the output is the notified relevant departments (e.g., warehouse managers and transportation department staff). Specifically, the server sends the final version of the document to the relevant parties using email or a chat system (e.g., Slack).

[0211] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0212] The present invention relates to a system that enables users to upload various sales-related documents from their terminals, and a server to analyze and process the documents to efficiently create and notify users, and also to a system that combines an emotion engine that recognizes the user's emotions and adjusts the content of the documents. The following describes in detail embodiments of the present invention.

[0213] Upload method

[0214] First, a user selects a document file (e.g., a CP document or a service proposal document) using a terminal and uploads it to the server. The uploaded document is saved on the server, and metadata such as the file name, user ID, and upload date and time are recorded along with it.

[0215] Information extraction method

[0216] The server analyzes the stored documents and uses natural language processing (NLP) techniques to extract important information from within the documents (e.g., product name, features, pricing, target market, etc.).

[0217] Emotion Engine Tools

[0218] The server also incorporates an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's input and actions to determine their emotional state. For example, it recognizes emotions based on the user's keyboard input speed and mouse movements as they review documents, as well as facial expression data obtained from a facial recognition camera.

[0219] Automated document generation methods

[0220] The server then refers to a past database and selects an appropriate document template based on the extracted important information and the user's emotions. The emotional information recognized by the emotion engine is reflected in the document generation process, and templates and wording appropriate to the user's emotions are selected.

[0221] User review and editing options

[0222] The generated document can be viewed by the user on their terminal, and they can edit the content as needed. The editing interface is designed for ease of use.

[0223] Document notification method

[0224] The server automatically notifies the relevant departments (such as the legal department or digital marketing department) of the final edited document via email or chat system, allowing the relevant parties to immediately check the contents of the new document.

[0225] Specific examples

[0226] For example, suppose User B uploads a service proposal document for a new product from their device. The server uses natural language processing technology to extract product features and pricing information from the document. At the same time, the emotion engine analyzes User B's keyboard typing speed and facial expressions and determines that User B is feeling stressed. Based on the extracted information and emotional information, the system selects templates from a past database designed to reduce stress and templates with a high concentration of gentle expressions, and automatically generates a new proposal document. User B can then review and edit the generated document on their device, and the final version can be automatically notified to the legal department and digital marketing department.

[0227] In this way, the present invention significantly improves the efficiency of document creation, enables detailed responses that take into account the user's emotional state, and provides a system that reduces errors and enables rapid information sharing.

[0228] The processing flow will be explained below.

[0229] Step 1:

[0230] The user selects a document file using the terminal and clicks the upload button. The terminal sends the selected document file and the user's ID to the server.

[0231] Step 2:

[0232] The server receives the uploaded document file and saves it in the specified storage. At the same time, the server records metadata such as the file name, user ID, and upload date and time in the database.

[0233] Step 3:

[0234] The server analyzes the stored document files and uses natural language processing (NLP) techniques to extract important information from within the documents (e.g., product name, features, pricing, target market, etc.) using techniques such as text mining and semantic analysis.

[0235] Step 4:

[0236] The emotion engine built into the server recognizes the user's emotions. The emotion engine performs emotion analysis based on the user's input speed, operation patterns, and data from the facial recognition camera. For example, it can read the user's facial expressions (joy, anger, sadness, and happiness) to determine the user's emotional state.

[0237] Step 5:

[0238] The server searches and selects the most appropriate document template from its historical database based on the extracted important information and the user's emotional data. If the emotion engine determines that the user is feeling stressed, it selects a template containing words and designs that have a relaxing effect.

[0239] Step 6:

[0240] The server then embeds the extracted key information into the selected template, creating a new, automatically generated document, placing the extracted information appropriately in placeholders within the template.

[0241] Step 7:

[0242] The server sends the automatically generated document to the user's device, where it can be viewed and edited. The user can view the document on their device and edit the content as necessary. This allows for document editing that is particularly conscious of reducing emotional stress.

[0243] Step 8:

[0244] The user then sends the edited document back to the server from the terminal. The server receives the edited document and saves it as the final version. It then receives a notification that editing is complete.

[0245] Step 9:

[0246] The server automatically notifies the relevant departments (e.g., legal department, digital marketing department) of the final version of the document. Notifications are sent via email or chat system, allowing the relevant parties to immediately check the contents of the new document. Along with notifications, the system also includes a function to report when the user's stress level has been reduced by the emotion engine.

[0247] Step 10:

[0248] The relevant departments will review the final document sent from the server and take any necessary action, completing the entire document creation and notification process.

[0249] Example 2

[0250] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0251] Conventional document creation systems automatically generate documents without taking the user's emotional state into consideration, making it difficult to respond flexibly to the user's mental state. Furthermore, checking and editing documents after generation is cumbersome, making it difficult to provide an efficient work environment. Furthermore, sharing generated documents with related departments is time-consuming, resulting in a lack of speed in information sharing.

[0252] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0253] In this invention, the server includes means for saving documents uploaded from terminals, means for extracting important information from the saved documents using natural language processing technology, means for automatically generating document templates based on the extracted information and referencing a past database, means for recognizing the user's emotional state and reflecting this in the selection of a document template, means for allowing the user to check and edit the automatically generated document, and means for automatically notifying relevant departments of the final document. This enables detailed document generation that takes the user's emotional state into consideration, efficient checking and editing, and rapid information sharing.

[0254] "Terminal" refers to a computer or smart device used by a user to upload documents to this system.

[0255] "Server" means a central computing device that stores and analyzes uploaded documents, and includes hardware and software for performing various system processes.

[0256] "Documents" refer to sales-related documents such as service proposal materials and CP materials, and are files that users upload to the system via their terminals.

[0257] "Natural language processing technology" refers to the technology that allows computers to understand and analyze human language, and is used to extract important information from documents.

[0258] "Important Information" refers to specific items contained within the document, such as product name, features, pricing, target market, etc.

[0259] The "emotion engine" is a system component that analyzes the user's input data and operation information and recognizes the user's emotional state.

[0260] A "template" refers to a format that defines a specific document format and is a framework for embedding extracted important information.

[0261] "Document template selection" is the process of determining an appropriate template based on the user's emotional state and information extracted from a historical database.

[0262] "Verifying and editing" refers to the process in which the user reviews the generated document on the terminal and corrects the content as necessary.

[0263] "Relevant departments" are departments that receive the generated documents, including, for example, the legal department and the digital marketing department.

[0264] "Notification" refers to the process of informing relevant departments of completed documents via email or chat system.

[0265] The present invention relates to a system that enables users to upload various sales-related documents from their terminals, and a server to analyze and process the documents to efficiently create and notify users, and also to a system that combines an emotion engine that recognizes the user's emotions and adjusts the content of the documents. The following describes in detail embodiments of the present invention.

[0266] System Configuration

[0267] Document Upload

[0268] First, a user uses a terminal to select a document file (e.g., a service proposal or CP document) and upload it to the server. The uploaded document is stored on the server, along with metadata such as the file name, user ID, and upload date and time. This upload process uses an HTTP POST request.

[0269] Information extraction using natural language processing

[0270] The server analyzes the uploaded documents and uses natural language processing technology to extract important information from within the documents (e.g., product name, features, pricing, target market, etc.). Specifically, analysis is performed using NLTK (Natural Language Toolkit), a Python natural language processing library. The extracted information is stored in a database for subsequent processing.

[0271] Emotion recognition by emotion engine

[0272] The server also incorporates an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's input and operations to determine their emotional state. Specifically, it uses keyboard input speed and mouse movements as the user reviews a document, as well as facial expression data obtained using OpenCV and facial recognition AI. This allows the server to determine the user's emotional state, such as whether they are feeling stressed.

[0273] Document template selection and auto-generation

[0274] The server selects an appropriate document template by referencing a past database based on the extracted important information and the user's emotional state. It selects a template that reflects the user's emotional state and automatically generates a new document based on that template. MySQL (registered trademark) is used for database management.

[0275] User review and editing

[0276] The generated document can be viewed on the user's device and edited as needed. The editing interface is built using JavaScript frameworks such as React and Vue.js, making it easy to use.

[0277] Document Notification

[0278] The server automatically notifies the relevant departments, including the legal department and digital marketing department, of the final edited document. Notifications are sent via email or chat systems such as Slack, allowing the relevant parties to immediately view the contents of the new document.

[0279] Specific examples

[0280] For example, suppose User B uploads a service proposal document for a new product from their device. The server extracts product features and pricing information from the document using Python's NLTK. At the same time, the emotion engine uses OpenCV and facial recognition AI to analyze User B's keyboard typing speed and facial expressions and determines that User B is feeling stressed. Based on the extracted information and emotional information, the server selects templates for stress reduction and templates with many softer expressions from a MySQL database and automatically generates new proposal documents. User B can review and edit the generated documents through an editing interface built with React or Vue.js, and the final version can be automatically notified to the legal department and digital marketing department via Slack.

[0281] This system significantly improves the efficiency of document creation, enabling detailed document generation according to the user's emotional state, and streamlines the review and editing process, enabling rapid information sharing.

[0282] Prompt Sentence Examples

[0283] "Please upload a service proposal document for a new product. The system will extract important information from the document and automatically generate a document that takes into account the user's emotional state using an emotion engine. The generated document can be viewed and edited on your device."

[0284] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0285] Step 1:

[0286] The user selects a document file using the terminal and uploads it to the server.

[0287] Input: A document file selected by the user, and an upload button operation.

[0288] Data processing and calculation: The user selects a file through a dedicated interface, and the file and its metadata (file name, user ID, upload date and time) are sent to the server via an HTTP POST request.

[0289] Output: Document files and metadata are saved on the server.

[0290] Specific operation: The user accesses the upload screen, clicks the "Choose File" button to select a document file, and then presses the "Upload" button to send the file to the server.

[0291] Step 2:

[0292] The server analyzes the uploaded documents and extracts key information using natural language processing techniques.

[0293] Input: A document file stored on the server.

[0294] Data processing and calculation: Uses Python's natural language processing library NLTK to extract important information from document content, such as product names, features, pricing, and target markets.

[0295] Output: The extracted important information is stored in a database.

[0296] Specific operation: After receiving the document, the server uses NLTK to analyze the content and extract the necessary information, which is then stored in a database.

[0297] Step 3:

[0298] The server uses an emotion engine to recognize the user's emotional state.

[0299] Input: User keyboard typing speed, mouse movements, and facial expression data.

[0300] Data processing and calculation: OpenCV and facial expression recognition AI are used to analyze this data and determine the user's emotional state.

[0301] Output: User's emotional state information is obtained.

[0302] How it works: The server monitors the user's keyboard input speed and mouse movements, analyzes the user's facial expressions using facial recognition AI, and combines this information to determine the user's emotional state.

[0303] Step 4:

[0304] Based on the information and emotional state extracted by the server, a document template is selected and automatically generated.

[0305] Input: Extracted important information, user emotional state information.

[0306] Data processing and calculation: By referring to the past database, a template suitable for the extracted information and emotional state is selected, and the necessary information is embedded in the template to automatically generate a document.

[0307] Output: Auto-generated documentation.

[0308] Specific operation: The server searches the database, selects an appropriate template, and generates a document by embedding the extracted information in the selected template.

[0309] Step 5:

[0310] The user checks and edits the generated document on the terminal.

[0311] Input: The generated document sent from the server.

[0312] Data processing and calculation: The user checks the document contents and edits them as necessary using the mouse and keyboard.

[0313] Output: The final edited document.

[0314] Specific operation: The user checks the generated document on the device, reviews the content, clicks to select the necessary parts, and makes corrections using the keyboard.

[0315] Step 6:

[0316] The server automatically notifies the relevant departments of the final edited document.

[0317] Input: The final document edited and saved by the user.

[0318] Data processing and calculation: The server sends the final document to the relevant department via email or chat system (e.g., Slack).

[0319] Output: Final document notified to relevant departments.

[0320] Specific operation: When the user completes editing and presses the "Send" button, the server receives the final document and notifies the relevant departments via email or Slack.

[0321] (Application example 2)

[0322] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0323] In conventional document creation systems, users had to manually create, edit, and notify multiple documents, which was a cumbersome process. It was also difficult to create documents that took into account the user's feelings and state, and the fine-tuned wording required to improve the quality of customer service was insufficient. This placed a heavy burden on users and made it difficult to efficiently manage business operations.

[0324] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0325] In this invention, the server includes means for saving documents uploaded from terminals, means for extracting important information from the saved documents, means for automatically generating document templates based on the extracted information and referencing a past database, means for allowing users to check and edit the automatically generated documents, means for automatically notifying relevant departments of the final document, and means for recognizing the user's emotions and adjusting the document content, thereby enabling efficient document creation and rapid information sharing that take the user's emotional state into consideration.

[0326] "Documents uploaded from a terminal" refers to document files transferred from the electronic device used by the user to the server via a network.

[0327] "Storage means" refers to a storage device for holding documents uploaded to a server for a certain period of time, and a method for managing such storage.

[0328] "Means for extracting important information" refers to analytical methods or software that can extract specific important information from the document content.

[0329] A "historical database" refers to data storage that stores documents and related information created in the past.

[0330] "Means for automatically generating document templates" refers to a technology that uses a computer program to automatically create new document templates based on information from past databases.

[0331] "Means for viewing and editing" refers to an interface or software that allows a user to view the contents of the generated document and make corrections or changes as necessary.

[0332] "Means for automatically notifying relevant departments" refers to a system that automatically sends the final generated document to specific departments or personnel via email, chat application, etc.

[0333] "Means for recognizing user emotions and adjusting document content" refers to algorithms or software that analyze the user's emotional state based on input data or biometric information, and change the wording and content of the document accordingly.

[0334] The present invention is a system in which a user uploads various sales-related documents from a terminal, and a server analyzes and processes the documents to efficiently create and notify them. It also includes an emotion engine that recognizes the user's emotions and adjusts the content of the document. Specific embodiments for implementing the present invention are described below.

[0335] Upload and storage methods

[0336] Users use their terminals to select document files such as CP materials or service proposal materials and upload them to the server. The server stores the uploaded documents and records metadata such as the file name, user ID, and upload date and time. The hardware used in this process is the user's PC or smart device, as well as the server's storage device.

[0337] Information extraction method

[0338] The server analyzes the stored documents and extracts key information using natural language processing techniques (e.g., spaCy). This extracted information is used to extract specific keywords and phrases from the document content (e.g., product name, features, pricing, target market, etc.).

[0339] Emotion Engine Tools

[0340] The server is equipped with an emotion engine to recognize the user's emotions by using keystroke speed, mouse movements, and facial expression data obtained from a facial recognition camera (e.g., EmotionRecognizer) as the user reviews the document.

[0341] Automated document generation methods

[0342] The server automatically generates an appropriate document template based on the extracted information and the user's emotions, referencing a past database. The generated document adjusts the wording and expressions to take the user's emotional state into consideration.

[0343] User review and editing options

[0344] The generated document is then made available to the user on their device, where they can edit it as needed through an easy-to-use interface, either using dedicated document editing software or a web application.

[0345] Document notification method

[0346] The server automatically notifies the relevant departments (e.g., legal and marketing) of the final edited document via email or a chat system.

[0347] Specific examples

[0348] For example, consider a virtual store operator who answers customer questions in real time. The operator uses smart glasses or a head-mounted display to quickly generate and present relevant documents in response to the customer's question. In this case, the following prompt sentences are used:

[0349] Prompt example

[0350] I have uploaded the document with the information the customer is requesting:

[0351] Document Content: {Document Content}

[0352] User data: {typing speed, facial expressions, tone of voice}

[0353] Select the appropriate template and provide the generated document.

[0354] Produce effective documentation and emotionally sensitive briefings.

[0355] This system enables efficient document creation and rapid information sharing that takes into account the user's emotional state. It is also expected to improve the quality of customer service in virtual stores and increase user satisfaction.

[0356] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0357] Step 1:

[0358] The user uploads sales-related documents from the terminal.

[0359] Input: Document file (e.g., CP documents, service proposal documents)

[0360] Output: Document file sent to the server

[0361] Specific operation: The user selects a document file using the file selection dialog on the device and clicks the upload button. At that time, metadata such as the file name, user ID, and upload date and time are sent to the server.

[0362] Step 2:

[0363] The server stores the uploaded document file.

[0364] Input: Document files uploaded by users, along with associated metadata

[0365] Output: Document files and metadata stored in the server storage

[0366] Specific operation: The server receives the document file and metadata, saves the file in the specified directory, and stores the metadata in the database.

[0367] Step 3:

[0368] The server uses natural language processing techniques to extract important information from stored documents.

[0369] Input: Saved document file

[0370] Output: Extracted key information (e.g. product name, features, pricing, target market, etc.)

[0371] What it does: The server reads the document file and uses a natural language processing library (e.g., spaCy) to extract keywords and phrases from the document content. The extracted information is temporarily stored in memory.

[0372] Step 4:

[0373] The server activates an emotion engine that recognizes the user's emotions.

[0374] Input: User input data (e.g., keystroke speed, mouse movements, facial expressions, etc.)

[0375] Output: User's emotional state (e.g., stress, joy, concentration, etc.)

[0376] Specific operation: The server inputs the user's keystroke speed, mouse movements, and facial expression data obtained from a face recognition camera into an emotion recognition library (e.g., EmotionRecognizer) to determine the user's emotional state.

[0377] Step 5:

[0378] The server automatically generates a document template by referencing a past database based on the extracted information and the user's emotional state.

[0379] Input: Extracted important information, user's emotional state, historical database

[0380] Output: Auto-generated document template

[0381] Specific operation: The server searches the past database based on the extracted information and emotional state, selects an appropriate document template, embeds the extracted information in the template, and generates a new document.

[0382] Step 6:

[0383] The user reviews and edits the generated document.

[0384] Input: Auto-generated document template

[0385] Output: The final document reviewed and edited by the user

[0386] Specific operation: The user checks the automatically generated document through the editing interface on the terminal and edits the content as necessary. The changes are updated in real time on the server.

[0387] Step 7:

[0388] The server automatically notifies the relevant departments of the final document.

[0389] Input: Final document edited by the user

[0390] Output: Final document notified to relevant departments

[0391] Specific Actions: The server automatically sends the final document to the relevant departments (e.g., legal department, marketing department) via email or chat system, and provides feedback to the user that the notification has been completed.

[0392] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0393] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0394] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0395] [Second embodiment]

[0396] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0397] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0398] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0399] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0400] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0401] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0402] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0403] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0404] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0405] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0406] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0407] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0408] The present invention relates to a system that enables users to upload various sales-related documents from their terminals and a server to analyze and process the documents, thereby achieving efficient document creation and notification. The following describes in detail an embodiment of the present invention.

[0409] Upload method

[0410] First, a user selects a document file (e.g., a CP document or a service proposal document) using a terminal and uploads it to the server. The uploaded document is saved on the server, and metadata such as the file name, user ID, and upload date and time are recorded along with it.

[0411] Information extraction method

[0412] The server analyzes the stored documents and uses natural language processing techniques to extract key information, such as product name, features, pricing, target market, etc.

[0413] Automated document generation methods

[0414] Next, the server selects an appropriate document template based on the extracted important information by referencing the historical database, and automatically generates a new document by embedding the extracted information into the template.

[0415] User review and editing options

[0416] The generated document can be viewed by the user on their device, and they can edit the content as needed. The editing interface is designed for ease of use.

[0417] Document notification method

[0418] The server automatically notifies the relevant departments of the final edited document via email or chat, allowing departments such as the legal department and digital marketing department to instantly view the new document contents.

[0419] Specific examples

[0420] For example, suppose User A uploads a service proposal document for a new product from their device. The server uses natural language processing technology to extract product features and pricing information from the document. Based on the extracted information, the server references proposal document templates from past similar products and automatically generates a new proposal document. User A reviews the generated document on their device and makes any necessary corrections, after which the server automatically notifies the legal department and digital marketing department of the final version.

[0421] In this way, the present invention provides a system that significantly improves the efficiency of document creation, reduces the occurrence of errors, and enables rapid information sharing.

[0422] The processing flow will be explained below.

[0423] Step 1:

[0424] The user selects a document file using the terminal and clicks the upload button. The terminal sends the selected file to the server.

[0425] Step 2:

[0426] The server receives the uploaded document file and saves it in storage. At the same time, the server records metadata such as the file name, user ID, and upload date and time in a database.

[0427] Step 3:

[0428] The server analyzes the stored document files and uses natural language processing (NLP) techniques to extract important information from within the documents (e.g., product name, features, pricing, target market).

[0429] Step 4:

[0430] Based on the extracted key information, the server searches for and selects the most similar document template by referring to a database of past development documents and templates.

[0431] Step 5:

[0432] The server then processes the selected template to embed the extracted important information, resulting in a new, automatically generated document.

[0433] Step 6:

[0434] The server sends the automatically generated document to the user's device, allowing the user to check the document contents. The user can then check the document on their device and edit it as necessary.

[0435] Step 7:

[0436] The user edits the document and sends it to the server, which receives the edits and saves them as the final document.

[0437] Step 8:

[0438] The server automatically notifies the relevant departments (e.g., legal department, digital marketing department) of the final document via email or chat system, allowing the relevant parties to instantly check the document contents.

[0439] Example 1

[0440] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0441] In conventional document creation systems, the processes of document uploading, analysis, generation, editing, and notification are fragmented, resulting in low overall efficiency and delays in information sharing. Furthermore, systems that automate document creation by applying natural language processing and generative AI models are not yet widespread, resulting in a heavy burden on human resources. The present invention aims to solve these issues and significantly improve the efficiency of document creation and notification.

[0442] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0443] In this invention, the server includes means for saving documents uploaded from a terminal, means for extracting important information from the saved documents using natural language processing technology, means for automatically generating a document template based on the extracted information and referring to a past database, means for generating a document based on the extracted information using a generative AI model, means for allowing a user to check and edit the automatically generated document, means for automatically notifying relevant departments of the final document, and means for recording metadata of the saved document. This automates the entire process from document creation to notification, improving overall efficiency and enabling fast and accurate information sharing.

[0444] A "terminal" is an electronic device such as a computer or smartphone that is operated by a user.

[0445] A "server" is a computer system that receives data sent from a terminal via a network and performs various functions such as storage, analysis, processing, and notification.

[0446] A "document" is a collection of information stored in electronic file format, and includes sales-related materials, proposals, and the like.

[0447] "Saving" is the process of storing a document uploaded to a server in storage so that it can be accessed later.

[0448] "Metadata" is additional information associated with a document, including file name, user ID, upload date and time, etc.

[0449] "Natural language processing technology" is a technology that allows computers to understand human language and is used to extract important information from documents.

[0450] "Important Information" is information necessary to understand the significance of the document, such as the product name, features, pricing, target market, etc., contained within the document.

[0451] A "database" is a system that stores multiple data in an organized manner and allows them to be searched and accessed efficiently.

[0452] A "document template" is a model of a document with a standard format and structure, and serves as the basis for creating a new document.

[0453] A "generative AI model" is an artificial intelligence model that uses machine learning and deep learning to automatically generate new documents.

[0454] "Validation" is the process in which a user checks the content of a generated document and considers its accuracy and suitability.

[0455] "Editing" is the process by which a user changes or modifies the content of a generated document.

[0456] "Notification" is the process of informing relevant departments of the final completed document, and is mainly done via email or chat systems.

[0457] "Related departments" are departments responsible for work related to the generated documents, such as the legal department and the digital marketing department.

[0458] MODE FOR CARRYING OUT THE INVENTION

[0459] The present invention relates to a system that enables efficient document creation and notification by allowing users to upload sales-related documents from their terminals and having a server analyze and process the documents. The following describes in detail an embodiment of the present invention.

[0460] Upload method

[0461] First, the user uses the terminal to select a current sales-related document (e.g., CP document or service proposal document) and upload it to the server. In this upload process, the user opens a file selection dialog on the terminal screen and selects the desired document file. Once the document file is selected, the user clicks the "Upload" button to send the document to the server.

[0462] Preservation and metadata recording methods

[0463] The server receives the document file sent from the device and saves the document in a specific directory. At the same time, it records metadata such as the file name, user ID, and upload date and time in a database (e.g., an SQL database). In this step, the server uses an appropriate SQL query to insert the metadata into the database, allowing the document to be easily searched and referenced later.

[0464] Means of Information Extraction

[0465] The server analyzes the stored documents using natural language processing (NLP) technology (e.g., TensorFlow, SpaCy) to extract important information. This important information includes product names, features, pricing, target markets, etc. Specifically, the NLP engine tokenizes the documents and analyzes the meaning of each token. The analysis results are stored in a database as structured data.

[0466] Means of automatic document generation

[0467] Next, the server selects an appropriate document template based on the extracted key information by referencing a historical database (e.g., MongoDB or SQL database). Once a template is selected, the server provides the information to a generative AI model (e.g., OpenAI's GPT-4) to automatically generate a new document. Specifically, the server embeds the information into the template and outputs it as the final document format.

[0468] User review and editing means

[0469] The generated document is displayed on the user's device, where the user can review the content and make edits as necessary. The user can directly modify each field of the document through the web browser interface. After completing the modifications, the user clicks the "Save" button to send the changes to the server.

[0470] Final Document Notification Method

[0471] Once the user has finished editing the document, it is saved back to the server. The server then automatically notifies the relevant departments of the final version of the document. This notification is done by sending email using the SMTP protocol or by sending a chat message using the Slack API. Specifically, the server obtains the notification address and sends an email or chat message.

[0472] Specific examples

[0473] For example, suppose User A uploads a service proposal document for a new product from their device. The server receives the document and uses natural language processing technology to extract product features and pricing information. Based on the extracted information, the server references past proposal document templates for similar products and generates a new proposal document. User A then reviews the generated document on their device and makes any necessary corrections. Finally, the server notifies the legal department and digital marketing department of the completed document.

[0474] Prompt Sentence Examples

[0475] "Generate a service proposal for a new product. Create the proposal using the following information:

[0476] Product Name: Product X

[0477] Features: high speed processing, low power consumption

[0478] Price: 50,000 yen

[0479] Target market: Small and medium-sized businesses

[0480] Please embed this information in your pitch deck template."

[0481] Thus, the present invention automates each step of the document creation process, greatly improving efficiency.

[0482] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0483] Step 1:

[0484] The user selects a document file (e.g., CP materials or service proposal materials) using the terminal and clicks the "Upload" button. This sends the document file selected through the file selection dialog to the server.

[0485] Input: A document file selected by the user

[0486] Output: The document file sent to the server

[0487] Step 2:

[0488] The server saves the received document file in a specific directory. It also records metadata such as the file name, user ID, and upload date and time in a database. For this purpose, it uses an SQL database to store the metadata. The server receives an HTTP POST request and processes the document file and metadata included in the request.

[0489] Input: Document file sent from the device, metadata (file name, user ID, upload date and time)

[0490] Output: Saved document files, metadata recorded in a database

[0491] Step 3:

[0492] The server analyzes the stored documents using natural language processing techniques (e.g., TensorFlow, SpaCy) to extract important information. The server tokenizes the document text and extracts information based on specific patterns or keywords.

[0493] Input: Saved document file

[0494] Output: Extracted key information (product name, features, pricing, target market)

[0495] Step 4:

[0496] Based on the extracted information, the server selects an appropriate document template by referencing a historical database (e.g., MongoDB, SQL database). The server executes a database query to search and retrieve similar historical document templates.

[0497] Input: Extracted important information

[0498] Output: Selected document template

[0499] Step 5:

[0500] The server uses a generative AI model (e.g., OpenAI's GPT-4) to automatically generate new documents. Specifically, it inputs the extracted information as prompts into the generative AI model and embeds the generated document text into a template.

[0501] Input: Selected document template, extracted key information

[0502] Output: Auto-generated document

[0503] Step 6:

[0504] The generated document is displayed on the user's device, where the user can review the content and edit it as necessary. The user can also directly modify the document text through the web browser interface.

[0505] Input: Auto-generated document

[0506] Output: The corrected document

[0507] Step 7:

[0508] Once the user has completed the revisions, the document is saved back to the server, which then automatically notifies the relevant departments of the final version of the document and sends an email or chat message using an SMTP server or Slack API.

[0509] Input: revised document, contact information of relevant departments

[0510] Output: Final document notified to relevant departments

[0511] This series of processes automates and efficiently executes the process from when a user uploads a document to when the server analyzes, generates, and notifies the user.

[0512] (Application example 1)

[0513] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0514] In today's logistics centers, the creation and management of a wide variety of business-related documents is required. However, manual document creation is time-consuming and carries a high risk of errors. Furthermore, delayed sharing of information reduces operational efficiency. There is a need for a method to solve these problems and achieve efficient and accurate document creation and rapid information sharing.

[0515] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0516] In this invention, the server includes means for saving documents uploaded from terminals, means for extracting important information from the saved documents, means for automatically generating document templates by referencing a past database based on the extracted information, means for allowing users to check and edit the automatically generated documents, means for automatically notifying relevant departments of the final documents, means for extracting important logistics information (product name, quantity, date of receipt, etc.) from the documents and automatically generating an appropriate inventory report template if the documents include business-related documents used in the logistics center, and means for allowing users to check and edit the documents generated on their smart devices. This improves the efficiency of business document creation in logistics centers, reduces errors, and enables rapid information sharing.

[0517] A "terminal" is an electronic device such as a computer or smartphone used by a user.

[0518] A "document" is a digital file that consists of text, images, etc.

[0519] "Saving" refers to the act of recording an uploaded document in a storage device within the server.

[0520] "Extraction" is the act of analyzing and extracting important information from within a document.

[0521] "Natural language processing technology" is a technology that allows computers to analyze and understand natural language.

[0522] A "database" is a collection of documents and information that have been stored in the past.

[0523] A "document template" is a pattern that defines the format and structure of a document.

[0524] "Automatic generation" refers to the act of a computer creating a document based on extracted information.

[0525] "Verification" is the act of a user reviewing the generated document.

[0526] "Editing" is an action in which a user modifies the content of a generated document.

[0527] "Notification" is the act of communicating to report the generated document to the relevant department.

[0528] A "logistics center" is a facility that handles logistics operations such as receiving, storing, and shipping goods.

[0529] "Business-related documents" are documents necessary for carrying out daily business.

[0530] A "smart device" is a mobile information terminal with advanced functions, such as a smartphone or tablet.

[0531] An "inventory report" is a document used to record inventory status.

[0532] In the system realizing the present invention, the following elements are used to automatically generate and notify documents.

[0533] Hardware and software used

[0534] 1. Hardware:

[0535] Smart devices (smartphones and tablets)

[0536] server

[0537] 2. Software:

[0538] Python

[0539] Django (server-side framework)

[0540] NLTK (Natural Language Processing Library)

[0541] React Native (application development for smart devices)

[0542] Data processing and calculation

[0543] Upload method

[0544] Users use their smart devices to select business-related documents (e.g., inventory lists and outbound lists) and upload them to the server. The React Native application makes it easy to select and upload files.

[0545] Preservation methods

[0546] Uploaded documents are stored in a database on the server using the Django framework, along with metadata such as file name, user ID, and upload date and time.

[0547] Information extraction method

[0548] The stored documents are analyzed on the server using Python and NLTK, and key logistics information such as product name, quantity, and receipt date is extracted from the documents using natural language processing technology.

[0549] Automated document generation methods

[0550] Based on the extracted information, the server selects an appropriate inventory report template from the historical database, and by filling in the extracted information in the template, a new business document is automatically generated.

[0551] User review and editing options

[0552] The generated documentation is made available for users to view on their smart devices, and users can edit the generated documentation using a React Native application.

[0553] Document notification method

[0554] The server automatically notifies the relevant departments of the final edited version via email or chat system (e.g., Slack), allowing warehouse managers and transportation staff to instantly check the contents of the new document.

[0555] Specific examples

[0556] As an example, consider the case where User B at a logistics center uploads a list of products received that day. The server uses natural language processing technology to extract important information from the list, such as product name, quantity, and receiving date. Next, it automatically generates a new report by filling in an appropriate inventory report template based on the extracted information. User B checks the generated report using a smart device and makes any necessary corrections. The server then automatically notifies the warehouse manager and transportation department staff of the corrected report.

[0557] Prompt Sentence Examples

[0558] "Develop a program to automatically generate inventory reports for a distribution center. Follow these steps:

[0559] 1. Upload business-related documents (stock receipt lists and stock issue lists) from your smart device.

[0560] 2. Extract key information from documents, such as product name, quantity, and receipt date, using natural language processing.

[0561] 3. Based on the extracted information, select an appropriate inventory report template and automatically generate a new document.

[0562] 4. Allow users to view and edit the generated documents on their smart devices.

[0563] 5. Notify the warehouse manager and transportation department staff of the edited document.

[0564] This invention improves the efficiency of business document creation at logistics centers, reduces errors, and enables quick information sharing.

[0565] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0566] Step 1:

[0567] A user uses a smart device to select business-related documents (e.g., inventory receipt list or inventory issue list) and upload them to the server. The input is the document file, and the output is the transfer of the document file to the server. The selection and uploading are performed through a React Native application on the smart device.

[0568] Step 2:

[0569] The server uses the Django framework to store the uploaded document in a database. The input is the uploaded document file and its metadata (file name, user ID, upload date and time, etc.), and the output is a record of the document and its metadata in the database. Specifically, the server stores the document data and its metadata in the database.

[0570] Step 3:

[0571] The server analyzes the stored documents using natural language processing technology and extracts important logistics information (product name, quantity, date of receipt, etc.). The input is the document file stored in the database, and the output is the extracted important information. Specifically, the server uses Python and NLTK to analyze the documents and extract the specified information.

[0572] Step 4:

[0573] The server selects an appropriate inventory report template based on the information extracted from the historical database and automatically generates a new business document. The input is the extracted important information and the template database, and the output is the newly generated business document. Specifically, the server embeds the extracted information into the template to create a new document.

[0574] Step 5:

[0575] The server sends the generated business document to the smart device for the user to review and edit. The input is the generated document, and the output is the document modified by the user. Specifically, the user uses a React Native application on the smart device to review the generated document and make any necessary edits.

[0576] Step 6:

[0577] The server automatically notifies the relevant departments of the final version of the document. The input is the final version of the document modified by the user, and the output is the notified relevant departments (e.g., warehouse managers and transportation department staff). Specifically, the server sends the final version of the document to the relevant parties using email or a chat system (e.g., Slack).

[0578] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0579] The present invention relates to a system that enables users to upload various sales-related documents from their terminals, and a server to analyze and process the documents to efficiently create and notify users, and also to a system that combines an emotion engine that recognizes the user's emotions and adjusts the content of the documents. The following describes in detail embodiments of the present invention.

[0580] Upload method

[0581] First, a user selects a document file (e.g., a CP document or a service proposal document) using a terminal and uploads it to the server. The uploaded document is saved on the server, and metadata such as the file name, user ID, and upload date and time are recorded along with it.

[0582] Information extraction method

[0583] The server analyzes the stored documents and uses natural language processing (NLP) techniques to extract important information from within the documents (e.g., product name, features, pricing, target market, etc.).

[0584] Emotion Engine Tools

[0585] The server also incorporates an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's input and actions to determine their emotional state. For example, it recognizes emotions based on the user's keyboard input speed and mouse movements as they review documents, as well as facial expression data obtained from a facial recognition camera.

[0586] Automated document generation methods

[0587] The server then refers to a past database and selects an appropriate document template based on the extracted important information and the user's emotions. The emotional information recognized by the emotion engine is reflected in the document generation process, and templates and wording appropriate to the user's emotions are selected.

[0588] User review and editing options

[0589] The generated document can be viewed by the user on their terminal, and they can edit the content as needed. The editing interface is designed for ease of use.

[0590] Document notification method

[0591] The server automatically notifies the relevant departments (such as the legal department or digital marketing department) of the final edited document via email or chat system, allowing the relevant parties to immediately check the contents of the new document.

[0592] Specific examples

[0593] For example, suppose User B uploads a service proposal document for a new product from their device. The server uses natural language processing technology to extract product features and pricing information from the document. At the same time, the emotion engine analyzes User B's keyboard typing speed and facial expressions and determines that User B is feeling stressed. Based on the extracted information and emotional information, the system selects templates from a past database designed to reduce stress and templates with a high concentration of gentle expressions, and automatically generates a new proposal document. User B can then review and edit the generated document on their device, and the final version can be automatically notified to the legal department and digital marketing department.

[0594] In this way, the present invention significantly improves the efficiency of document creation, enables detailed responses that take into account the user's emotional state, and provides a system that reduces errors and enables rapid information sharing.

[0595] The processing flow will be explained below.

[0596] Step 1:

[0597] The user selects a document file using the terminal and clicks the upload button. The terminal sends the selected document file and the user's ID to the server.

[0598] Step 2:

[0599] The server receives the uploaded document file and saves it in the specified storage. At the same time, the server records metadata such as the file name, user ID, and upload date and time in the database.

[0600] Step 3:

[0601] The server analyzes the stored document files and uses natural language processing (NLP) techniques to extract important information from within the documents (e.g., product name, features, pricing, target market, etc.) using techniques such as text mining and semantic analysis.

[0602] Step 4:

[0603] The emotion engine built into the server recognizes the user's emotions. The emotion engine performs emotion analysis based on the user's input speed, operation patterns, and data from the facial recognition camera. For example, it can read the user's facial expressions (joy, anger, sadness, and happiness) to determine the user's emotional state.

[0604] Step 5:

[0605] The server searches and selects the most appropriate document template from its historical database based on the extracted important information and the user's emotional data. If the emotion engine determines that the user is feeling stressed, it selects a template containing words and designs that have a relaxing effect.

[0606] Step 6:

[0607] The server then embeds the extracted key information into the selected template, creating a new, automatically generated document, placing the extracted information appropriately in placeholders within the template.

[0608] Step 7:

[0609] The server sends the automatically generated document to the user's device, where it can be viewed and edited. The user can view the document on their device and edit the content as necessary. This allows for document editing that is particularly conscious of reducing emotional stress.

[0610] Step 8:

[0611] The user then sends the edited document back to the server from the terminal. The server receives the edited document and saves it as the final version. It then receives a notification that editing is complete.

[0612] Step 9:

[0613] The server automatically notifies the relevant departments (e.g., legal department, digital marketing department) of the final version of the document. Notifications are sent via email or chat system, allowing the relevant parties to immediately check the contents of the new document. Along with notifications, the system also includes a function to report when the user's stress level has been reduced by the emotion engine.

[0614] Step 10:

[0615] The relevant departments will review the final document sent from the server and take any necessary action, completing the entire document creation and notification process.

[0616] Example 2

[0617] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0618] Conventional document creation systems automatically generate documents without taking the user's emotional state into consideration, making it difficult to respond flexibly to the user's mental state. Furthermore, checking and editing documents after generation is cumbersome, making it difficult to provide an efficient work environment. Furthermore, sharing generated documents with related departments is time-consuming, resulting in a lack of speed in information sharing.

[0619] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0620] In this invention, the server includes means for saving documents uploaded from terminals, means for extracting important information from the saved documents using natural language processing technology, means for automatically generating document templates based on the extracted information and referencing a past database, means for recognizing the user's emotional state and reflecting this in the selection of a document template, means for allowing the user to check and edit the automatically generated document, and means for automatically notifying relevant departments of the final document. This enables detailed document generation that takes the user's emotional state into consideration, efficient checking and editing, and rapid information sharing.

[0621] "Terminal" refers to a computer or smart device used by a user to upload documents to this system.

[0622] "Server" means a central computing device that stores and analyzes uploaded documents, and includes hardware and software for performing various system processes.

[0623] "Documents" refer to sales-related documents such as service proposal materials and CP materials, and are files that users upload to the system via their terminals.

[0624] "Natural language processing technology" refers to the technology that allows computers to understand and analyze human language, and is used to extract important information from documents.

[0625] "Important Information" refers to specific items contained within the document, such as product name, features, pricing, target market, etc.

[0626] The "emotion engine" is a system component that analyzes the user's input data and operation information and recognizes the user's emotional state.

[0627] A "template" refers to a format that defines a specific document format and is a framework for embedding extracted important information.

[0628] "Document template selection" is the process of determining an appropriate template based on the user's emotional state and information extracted from a historical database.

[0629] "Verifying and editing" refers to the process in which the user reviews the generated document on the terminal and corrects the content as necessary.

[0630] "Relevant departments" are departments that receive the generated documents, including, for example, the legal department and the digital marketing department.

[0631] "Notification" refers to the process of informing relevant departments of completed documents via email or chat system.

[0632] The present invention relates to a system that enables users to upload various sales-related documents from their terminals, and a server to analyze and process the documents to efficiently create and notify users, and also to a system that combines an emotion engine that recognizes the user's emotions and adjusts the content of the documents. The following describes in detail embodiments of the present invention.

[0633] System Configuration

[0634] Document Upload

[0635] First, a user uses a terminal to select a document file (e.g., a service proposal or CP document) and upload it to the server. The uploaded document is stored on the server, along with metadata such as the file name, user ID, and upload date and time. This upload process uses an HTTP POST request.

[0636] Information extraction using natural language processing

[0637] The server analyzes the uploaded documents and uses natural language processing technology to extract important information from within the documents (e.g., product name, features, pricing, target market, etc.). Specifically, analysis is performed using NLTK (Natural Language Toolkit), a Python natural language processing library. The extracted information is stored in a database for subsequent processing.

[0638] Emotion recognition by emotion engine

[0639] The server also incorporates an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's input and operations to determine their emotional state. Specifically, it uses keyboard input speed and mouse movements as the user reviews a document, as well as facial expression data obtained using OpenCV and facial recognition AI. This allows the server to determine the user's emotional state, such as whether they are feeling stressed.

[0640] Document template selection and auto-generation

[0641] The server selects an appropriate document template by referring to the past database based on the extracted important information and the user's emotional state. It selects a template that reflects the user's emotional state and automatically generates a new document based on that template. MySQL is used for database management.

[0642] User review and editing

[0643] The generated document can be viewed on the user's device and edited as needed. The editing interface is built using JavaScript frameworks such as React and Vue.js, with ease of use in mind.

[0644] Document Notification

[0645] The server automatically notifies the relevant departments, including the legal department and digital marketing department, of the final edited document. Notifications are sent via email or chat systems such as Slack, allowing the relevant parties to immediately view the contents of the new document.

[0646] Specific examples

[0647] For example, suppose User B uploads a service proposal document for a new product from their device. The server extracts product features and pricing information from the document using Python's NLTK. At the same time, the emotion engine uses OpenCV and facial recognition AI to analyze User B's keyboard typing speed and facial expressions and determines that User B is feeling stressed. Based on the extracted information and emotional information, the server selects templates for stress reduction and templates with many softer expressions from a MySQL database and automatically generates new proposal documents. User B can review and edit the generated documents through an editing interface built with React or Vue.js, and the final version can be automatically notified to the legal department and digital marketing department via Slack.

[0648] This system significantly improves the efficiency of document creation, enabling detailed document generation according to the user's emotional state, and streamlines the review and editing process, enabling rapid information sharing.

[0649] Prompt Sentence Examples

[0650] "Please upload a service proposal document for a new product. The system will extract important information from the document and automatically generate a document that takes into account the user's emotional state using an emotion engine. The generated document can be viewed and edited on your device."

[0651] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0652] Step 1:

[0653] The user selects a document file using the terminal and uploads it to the server.

[0654] Input: A document file selected by the user, and an upload button operation.

[0655] Data processing and calculation: The user selects a file through a dedicated interface, and the file and its metadata (file name, user ID, upload date and time) are sent to the server via an HTTP POST request.

[0656] Output: Document files and metadata are saved on the server.

[0657] Specific operation: The user accesses the upload screen, clicks the "Choose File" button to select a document file, and then presses the "Upload" button to send the file to the server.

[0658] Step 2:

[0659] The server analyzes the uploaded documents and extracts key information using natural language processing techniques.

[0660] Input: A document file stored on the server.

[0661] Data processing and calculation: Uses Python's natural language processing library NLTK to extract important information from document content, such as product names, features, pricing, and target markets.

[0662] Output: The extracted important information is stored in a database.

[0663] Specific operation: After receiving the document, the server uses NLTK to analyze the content and extract the necessary information, which is then stored in a database.

[0664] Step 3:

[0665] The server uses an emotion engine to recognize the user's emotional state.

[0666] Input: User keyboard typing speed, mouse movements, and facial expression data.

[0667] Data processing and calculation: OpenCV and facial expression recognition AI are used to analyze this data and determine the user's emotional state.

[0668] Output: User's emotional state information is obtained.

[0669] How it works: The server monitors the user's keyboard input speed and mouse movements, analyzes the user's facial expressions using facial recognition AI, and combines this information to determine the user's emotional state.

[0670] Step 4:

[0671] Based on the information and emotional state extracted by the server, a document template is selected and automatically generated.

[0672] Input: Extracted important information, user emotional state information.

[0673] Data processing and calculation: By referring to the past database, a template suitable for the extracted information and emotional state is selected, and the necessary information is embedded in the template to automatically generate a document.

[0674] Output: Auto-generated documentation.

[0675] Specific operation: The server searches the database, selects an appropriate template, and generates a document by embedding the extracted information in the selected template.

[0676] Step 5:

[0677] The user checks and edits the generated document on the terminal.

[0678] Input: The generated document sent from the server.

[0679] Data processing and calculation: The user checks the document contents and edits them as necessary using the mouse and keyboard.

[0680] Output: The final edited document.

[0681] Specific operation: The user checks the generated document on the device, reviews the content, clicks to select the necessary parts, and makes corrections using the keyboard.

[0682] Step 6:

[0683] The server automatically notifies the relevant departments of the final edited document.

[0684] Input: The final document edited and saved by the user.

[0685] Data processing and calculation: The server sends the final document to the relevant department via email or chat system (e.g., Slack).

[0686] Output: Final document notified to relevant departments.

[0687] Specific operation: When the user completes editing and presses the "Send" button, the server receives the final document and notifies the relevant departments via email or Slack.

[0688] (Application example 2)

[0689] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0690] In conventional document creation systems, users had to manually create, edit, and notify multiple documents, which was a cumbersome process. It was also difficult to create documents that took into account the user's feelings and state, and the fine-tuned wording required to improve the quality of customer service was insufficient. This placed a heavy burden on users and made it difficult to efficiently manage business operations.

[0691] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0692] In this invention, the server includes means for saving documents uploaded from terminals, means for extracting important information from the saved documents, means for automatically generating document templates based on the extracted information and referencing a past database, means for allowing users to check and edit the automatically generated documents, means for automatically notifying relevant departments of the final document, and means for recognizing the user's emotions and adjusting the document content, thereby enabling efficient document creation and rapid information sharing that take the user's emotional state into consideration.

[0693] "Documents uploaded from a terminal" refers to document files transferred from the electronic device used by the user to the server via a network.

[0694] "Storage means" refers to a storage device for holding documents uploaded to a server for a certain period of time, and a method for managing such storage.

[0695] "Means for extracting important information" refers to analytical methods or software that can extract specific important information from the document content.

[0696] A "historical database" refers to data storage that stores documents and related information created in the past.

[0697] "Means for automatically generating document templates" refers to a technology that uses a computer program to automatically create new document templates based on information from past databases.

[0698] "Means for viewing and editing" refers to an interface or software that allows a user to view the contents of the generated document and make corrections or changes as necessary.

[0699] "Means for automatically notifying relevant departments" refers to a system that automatically sends the final generated document to specific departments or personnel via email, chat application, etc.

[0700] "Means for recognizing user emotions and adjusting document content" refers to algorithms or software that analyze the user's emotional state based on input data or biometric information, and change the wording and content of the document accordingly.

[0701] The present invention is a system in which a user uploads various sales-related documents from a terminal, and a server analyzes and processes the documents to efficiently create and notify them. It also includes an emotion engine that recognizes the user's emotions and adjusts the content of the document. Specific embodiments for implementing the present invention are described below.

[0702] Upload and storage methods

[0703] Users use their terminals to select document files such as CP materials or service proposal materials and upload them to the server. The server stores the uploaded documents and records metadata such as the file name, user ID, and upload date and time. The hardware used in this process is the user's PC or smart device, as well as the server's storage device.

[0704] Information extraction method

[0705] The server analyzes the stored documents and extracts key information using natural language processing techniques (e.g., spaCy). This extracted information is used to extract specific keywords and phrases from the document content (e.g., product name, features, pricing, target market, etc.).

[0706] Emotion Engine Tools

[0707] The server is equipped with an emotion engine to recognize the user's emotions by using keystroke speed, mouse movements, and facial expression data obtained from a facial recognition camera (e.g., EmotionRecognizer) as the user reviews the document.

[0708] Automated document generation methods

[0709] The server automatically generates an appropriate document template based on the extracted information and the user's emotions, referencing a past database. The generated document adjusts the wording and expressions to take the user's emotional state into consideration.

[0710] User review and editing options

[0711] The generated document is then made available to the user on their device, where they can edit it as needed through an easy-to-use interface, either using dedicated document editing software or a web application.

[0712] Document notification method

[0713] The server automatically notifies the relevant departments (e.g., legal and marketing) of the final edited document via email or a chat system.

[0714] Specific examples

[0715] For example, consider a virtual store operator who answers customer questions in real time. The operator uses smart glasses or a head-mounted display to quickly generate and present relevant documents in response to the customer's question. In this case, the following prompt sentences are used:

[0716] Prompt example

[0717] I have uploaded the document with the information the customer is requesting:

[0718] Document Content: {Document Content}

[0719] User data: {typing speed, facial expressions, tone of voice}

[0720] Select the appropriate template and provide the generated document.

[0721] Produce effective documentation and emotionally sensitive briefings.

[0722] This system enables efficient document creation and rapid information sharing that takes into account the user's emotional state. It is also expected to improve the quality of customer service in virtual stores and increase user satisfaction.

[0723] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0724] Step 1:

[0725] The user uploads sales-related documents from the terminal.

[0726] Input: Document file (e.g., CP documents, service proposal documents)

[0727] Output: Document file sent to the server

[0728] Specific operation: The user selects a document file using the file selection dialog on the device and clicks the upload button. At that time, metadata such as the file name, user ID, and upload date and time are sent to the server.

[0729] Step 2:

[0730] The server stores the uploaded document file.

[0731] Input: Document files uploaded by users, along with associated metadata

[0732] Output: Document files and metadata stored in the server storage

[0733] Specific operation: The server receives the document file and metadata, saves the file in the specified directory, and stores the metadata in the database.

[0734] Step 3:

[0735] The server uses natural language processing techniques to extract important information from stored documents.

[0736] Input: Saved document file

[0737] Output: Extracted key information (e.g. product name, features, pricing, target market, etc.)

[0738] What it does: The server reads the document file and uses a natural language processing library (e.g., spaCy) to extract keywords and phrases from the document content. The extracted information is temporarily stored in memory.

[0739] Step 4:

[0740] The server activates an emotion engine that recognizes the user's emotions.

[0741] Input: User input data (e.g., keystroke speed, mouse movements, facial expressions, etc.)

[0742] Output: User's emotional state (e.g., stress, joy, concentration, etc.)

[0743] Specific operation: The server inputs the user's keystroke speed, mouse movements, and facial expression data obtained from a face recognition camera into an emotion recognition library (e.g., EmotionRecognizer) to determine the user's emotional state.

[0744] Step 5:

[0745] The server automatically generates a document template by referencing a past database based on the extracted information and the user's emotional state.

[0746] Input: Extracted important information, user's emotional state, historical database

[0747] Output: Auto-generated document template

[0748] Specific operation: The server searches the past database based on the extracted information and emotional state, selects an appropriate document template, embeds the extracted information in the template, and generates a new document.

[0749] Step 6:

[0750] The user reviews and edits the generated document.

[0751] Input: Auto-generated document template

[0752] Output: The final document reviewed and edited by the user

[0753] Specific operation: The user checks the automatically generated document through the editing interface on the terminal and edits the content as necessary. The changes are updated in real time on the server.

[0754] Step 7:

[0755] The server automatically notifies the relevant departments of the final document.

[0756] Input: Final document edited by the user

[0757] Output: Final document notified to relevant departments

[0758] Specific Actions: The server automatically sends the final document to the relevant departments (e.g., legal department, marketing department) via email or chat system, and provides feedback to the user that the notification has been completed.

[0759] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0760] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0761] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0762] [Third embodiment]

[0763] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0764] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0765] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0766] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0767] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0768] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0769] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0770] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0771] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0772] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0773] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0774] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0775] The present invention relates to a system that enables users to upload various sales-related documents from their terminals and a server to analyze and process the documents, thereby achieving efficient document creation and notification. The following describes in detail an embodiment of the present invention.

[0776] Upload method

[0777] First, a user selects a document file (e.g., a CP document or a service proposal document) using a terminal and uploads it to the server. The uploaded document is saved on the server, and metadata such as the file name, user ID, and upload date and time are recorded along with it.

[0778] Information extraction method

[0779] The server analyzes the stored documents and uses natural language processing techniques to extract key information, such as product name, features, pricing, target market, etc.

[0780] Automated document generation methods

[0781] Next, the server selects an appropriate document template based on the extracted important information by referencing the historical database, and automatically generates a new document by embedding the extracted information into the template.

[0782] User review and editing options

[0783] The generated document can be viewed by the user on their device, and they can edit the content as needed. The editing interface is designed for ease of use.

[0784] Document notification method

[0785] The server automatically notifies the relevant departments of the final edited document via email or chat, allowing departments such as the legal department and digital marketing department to instantly view the new document contents.

[0786] Specific examples

[0787] For example, suppose User A uploads a service proposal document for a new product from their device. The server uses natural language processing technology to extract product features and pricing information from the document. Based on the extracted information, the server references proposal document templates from past similar products and automatically generates a new proposal document. User A reviews the generated document on their device and makes any necessary corrections, after which the server automatically notifies the legal department and digital marketing department of the final version.

[0788] In this way, the present invention provides a system that significantly improves the efficiency of document creation, reduces the occurrence of errors, and enables rapid information sharing.

[0789] The processing flow will be explained below.

[0790] Step 1:

[0791] The user selects a document file using the terminal and clicks the upload button. The terminal sends the selected file to the server.

[0792] Step 2:

[0793] The server receives the uploaded document file and saves it in storage. At the same time, the server records metadata such as the file name, user ID, and upload date and time in a database.

[0794] Step 3:

[0795] The server analyzes the stored document files and uses natural language processing (NLP) techniques to extract important information from within the documents (e.g., product name, features, pricing, target market).

[0796] Step 4:

[0797] Based on the extracted key information, the server searches for and selects the most similar document template by referring to a database of past development documents and templates.

[0798] Step 5:

[0799] The server then processes the selected template to embed the extracted important information, resulting in a new, automatically generated document.

[0800] Step 6:

[0801] The server sends the automatically generated document to the user's device, allowing the user to check the document contents. The user can then check the document on their device and edit it as necessary.

[0802] Step 7:

[0803] The user edits the document and sends it to the server, which receives the edits and saves them as the final document.

[0804] Step 8:

[0805] The server automatically notifies the relevant departments (e.g., legal department, digital marketing department) of the final document via email or chat system, allowing the relevant parties to instantly check the document contents.

[0806] Example 1

[0807] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0808] In conventional document creation systems, the processes of document uploading, analysis, generation, editing, and notification are fragmented, resulting in low overall efficiency and delays in information sharing. Furthermore, systems that automate document creation by applying natural language processing and generative AI models are not yet widespread, resulting in a heavy burden on human resources. The present invention aims to solve these issues and significantly improve the efficiency of document creation and notification.

[0809] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0810] In this invention, the server includes means for saving documents uploaded from a terminal, means for extracting important information from the saved documents using natural language processing technology, means for automatically generating a document template based on the extracted information and referring to a past database, means for generating a document based on the extracted information using a generative AI model, means for allowing a user to check and edit the automatically generated document, means for automatically notifying relevant departments of the final document, and means for recording metadata of the saved document. This automates the entire process from document creation to notification, improving overall efficiency and enabling fast and accurate information sharing.

[0811] A "terminal" is an electronic device such as a computer or smartphone that is operated by a user.

[0812] A "server" is a computer system that receives data sent from a terminal via a network and performs various functions such as storage, analysis, processing, and notification.

[0813] A "document" is a collection of information stored in electronic file format, and includes sales-related materials, proposals, and the like.

[0814] "Saving" is the process of storing a document uploaded to a server in storage so that it can be accessed later.

[0815] "Metadata" is additional information associated with a document, including file name, user ID, upload date and time, etc.

[0816] "Natural language processing technology" is a technology that allows computers to understand human language and is used to extract important information from documents.

[0817] "Important Information" is information necessary to understand the significance of the document, such as the product name, features, pricing, target market, etc., contained within the document.

[0818] A "database" is a system that stores multiple data in an organized manner and allows them to be searched and accessed efficiently.

[0819] A "document template" is a model of a document with a standard format and structure, and serves as the basis for creating a new document.

[0820] A "generative AI model" is an artificial intelligence model that uses machine learning and deep learning to automatically generate new documents.

[0821] "Validation" is the process in which a user checks the content of a generated document and considers its accuracy and suitability.

[0822] "Editing" is the process by which a user changes or modifies the content of a generated document.

[0823] "Notification" is the process of informing relevant departments of the final completed document, and is mainly done via email or chat systems.

[0824] "Related departments" are departments responsible for work related to the generated documents, such as the legal department and the digital marketing department.

[0825] MODE FOR CARRYING OUT THE INVENTION

[0826] The present invention relates to a system that enables efficient document creation and notification by allowing users to upload sales-related documents from their terminals and having a server analyze and process the documents. The following describes in detail an embodiment of the present invention.

[0827] Upload method

[0828] First, the user uses the terminal to select a current sales-related document (e.g., CP document or service proposal document) and upload it to the server. In this upload process, the user opens a file selection dialog on the terminal screen and selects the desired document file. Once the document file is selected, the user clicks the "Upload" button to send the document to the server.

[0829] Preservation and metadata recording methods

[0830] The server receives the document file sent from the device and saves the document in a specific directory. At the same time, it records metadata such as the file name, user ID, and upload date and time in a database (e.g., an SQL database). In this step, the server uses an appropriate SQL query to insert the metadata into the database, allowing the document to be easily searched and referenced later.

[0831] Means of Information Extraction

[0832] The server analyzes the stored documents using natural language processing (NLP) technology (e.g., TensorFlow, SpaCy) to extract important information. This important information includes product names, features, pricing, target markets, etc. Specifically, the NLP engine tokenizes the documents and analyzes the meaning of each token. The analysis results are stored in a database as structured data.

[0833] Means of automatic document generation

[0834] Next, the server selects an appropriate document template based on the extracted key information by referencing a historical database (e.g., MongoDB or SQL database). Once a template is selected, the server provides the information to a generative AI model (e.g., OpenAI's GPT-4) to automatically generate a new document. Specifically, the server embeds the information into the template and outputs it as the final document format.

[0835] User review and editing means

[0836] The generated document is displayed on the user's device, where the user can review the content and make edits as necessary. The user can directly modify each field of the document through the web browser interface. After completing the modifications, the user clicks the "Save" button to send the changes to the server.

[0837] Final Document Notification Method

[0838] Once the user has finished editing the document, it is saved back to the server. The server then automatically notifies the relevant departments of the final version of the document. This notification is done by sending email using the SMTP protocol or by sending a chat message using the Slack API. Specifically, the server obtains the notification address and sends an email or chat message.

[0839] Specific examples

[0840] For example, suppose User A uploads a service proposal document for a new product from their device. The server receives the document and uses natural language processing technology to extract product features and pricing information. Based on the extracted information, the server references past proposal document templates for similar products and generates a new proposal document. User A then reviews the generated document on their device and makes any necessary corrections. Finally, the server notifies the legal department and digital marketing department of the completed document.

[0841] Prompt Sentence Examples

[0842] "Generate a service proposal for a new product. Create the proposal using the following information:

[0843] Product Name: Product X

[0844] Features: high speed processing, low power consumption

[0845] Price: 50,000 yen

[0846] Target market: Small and medium-sized businesses

[0847] Please embed this information in your pitch deck template."

[0848] Thus, the present invention automates each step of the document creation process, greatly improving efficiency.

[0849] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0850] Step 1:

[0851] The user selects a document file (e.g., CP materials or service proposal materials) using the terminal and clicks the "Upload" button. This sends the document file selected through the file selection dialog to the server.

[0852] Input: A document file selected by the user

[0853] Output: The document file sent to the server

[0854] Step 2:

[0855] The server saves the received document file in a specific directory. It also records metadata such as the file name, user ID, and upload date and time in a database. For this purpose, it uses an SQL database to store the metadata. The server receives an HTTP POST request and processes the document file and metadata included in the request.

[0856] Input: Document file sent from the device, metadata (file name, user ID, upload date and time)

[0857] Output: Saved document files, metadata recorded in a database

[0858] Step 3:

[0859] The server analyzes the stored documents using natural language processing techniques (e.g., TensorFlow, SpaCy) to extract important information. The server tokenizes the document text and extracts information based on specific patterns or keywords.

[0860] Input: Saved document file

[0861] Output: Extracted key information (product name, features, pricing, target market)

[0862] Step 4:

[0863] Based on the extracted information, the server selects an appropriate document template by referencing a historical database (e.g., MongoDB, SQL database). The server executes a database query to search and retrieve similar historical document templates.

[0864] Input: Extracted important information

[0865] Output: Selected document template

[0866] Step 5:

[0867] The server uses a generative AI model (e.g., OpenAI's GPT-4) to automatically generate new documents. Specifically, it inputs the extracted information as prompts into the generative AI model and embeds the generated document text into a template.

[0868] Input: Selected document template, extracted key information

[0869] Output: Auto-generated document

[0870] Step 6:

[0871] The generated document is displayed on the user's device, where the user can review the content and edit it as necessary. The user can also directly modify the document text through the web browser interface.

[0872] Input: Auto-generated document

[0873] Output: The corrected document

[0874] Step 7:

[0875] Once the user has completed the revisions, the document is saved back to the server, which then automatically notifies the relevant departments of the final version of the document and sends an email or chat message using an SMTP server or Slack API.

[0876] Input: revised document, contact information of relevant departments

[0877] Output: Final document notified to relevant departments

[0878] This series of processes automates and efficiently executes the process from when a user uploads a document to when the server analyzes, generates, and notifies the user.

[0879] (Application example 1)

[0880] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0881] In today's logistics centers, the creation and management of a wide variety of business-related documents is required. However, manual document creation is time-consuming and carries a high risk of errors. Furthermore, delayed sharing of information reduces operational efficiency. There is a need for a method to solve these problems and achieve efficient and accurate document creation and rapid information sharing.

[0882] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0883] In this invention, the server includes means for saving documents uploaded from terminals, means for extracting important information from the saved documents, means for automatically generating document templates by referencing a past database based on the extracted information, means for allowing users to check and edit the automatically generated documents, means for automatically notifying relevant departments of the final documents, means for extracting important logistics information (product name, quantity, date of receipt, etc.) from the documents and automatically generating an appropriate inventory report template if the documents include business-related documents used in the logistics center, and means for allowing users to check and edit the documents generated on their smart devices. This improves the efficiency of business document creation in logistics centers, reduces errors, and enables rapid information sharing.

[0884] A "terminal" is an electronic device such as a computer or smartphone used by a user.

[0885] A "document" is a digital file that consists of text, images, etc.

[0886] "Saving" refers to the act of recording an uploaded document in a storage device within the server.

[0887] "Extraction" is the act of analyzing and extracting important information from within a document.

[0888] "Natural language processing technology" is a technology that allows computers to analyze and understand natural language.

[0889] A "database" is a collection of documents and information that have been stored in the past.

[0890] A "document template" is a pattern that defines the format and structure of a document.

[0891] "Automatic generation" refers to the act of a computer creating a document based on extracted information.

[0892] "Verification" is the act of a user reviewing the generated document.

[0893] "Editing" is an action in which a user modifies the content of a generated document.

[0894] "Notification" is the act of communicating to report the generated document to the relevant department.

[0895] A "logistics center" is a facility that handles logistics operations such as receiving, storing, and shipping goods.

[0896] "Business-related documents" are documents necessary for carrying out daily business.

[0897] A "smart device" is a mobile information terminal with advanced functions, such as a smartphone or tablet.

[0898] An "inventory report" is a document used to record inventory status.

[0899] In the system realizing the present invention, the following elements are used to automatically generate and notify documents.

[0900] Hardware and software used

[0901] 1. Hardware:

[0902] Smart devices (smartphones and tablets)

[0903] server

[0904] 2. Software:

[0905] Python

[0906] Django (server-side framework)

[0907] NLTK (Natural Language Processing Library)

[0908] React Native (application development for smart devices)

[0909] Data processing and calculation

[0910] Upload method

[0911] Users use their smart devices to select business-related documents (e.g., inventory lists and outbound lists) and upload them to the server. The React Native application makes it easy to select and upload files.

[0912] Preservation methods

[0913] Uploaded documents are stored in a database on the server using the Django framework, along with metadata such as file name, user ID, and upload date and time.

[0914] Information extraction method

[0915] The stored documents are analyzed on the server using Python and NLTK, and key logistics information such as product name, quantity, and receipt date is extracted from the documents using natural language processing technology.

[0916] Automated document generation methods

[0917] Based on the extracted information, the server selects an appropriate inventory report template from the historical database, and by filling in the extracted information in the template, a new business document is automatically generated.

[0918] User review and editing options

[0919] The generated documentation is made available for users to view on their smart devices, and users can edit the generated documentation using a React Native application.

[0920] Document notification method

[0921] The server automatically notifies the relevant departments of the final edited version via email or chat system (e.g., Slack), allowing warehouse managers and transportation staff to instantly check the contents of the new document.

[0922] Specific examples

[0923] As an example, consider the case where User B at a logistics center uploads a list of products received that day. The server uses natural language processing technology to extract important information from the list, such as product name, quantity, and receiving date. Next, it automatically generates a new report by filling in an appropriate inventory report template based on the extracted information. User B checks the generated report using a smart device and makes any necessary corrections. The server then automatically notifies the warehouse manager and transportation department staff of the corrected report.

[0924] Prompt Sentence Examples

[0925] "Develop a program to automatically generate inventory reports for a distribution center. Follow these steps:

[0926] 1. Upload business-related documents (stock receipt lists and stock issue lists) from your smart device.

[0927] 2. Extract key information from documents, such as product name, quantity, and receipt date, using natural language processing.

[0928] 3. Based on the extracted information, select an appropriate inventory report template and automatically generate a new document.

[0929] 4. Allow users to view and edit the generated documents on their smart devices.

[0930] 5. Notify the warehouse manager and transportation department staff of the edited document.

[0931] This invention improves the efficiency of business document creation at logistics centers, reduces errors, and enables quick information sharing.

[0932] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0933] Step 1:

[0934] A user uses a smart device to select business-related documents (e.g., inventory receipt list or inventory issue list) and upload them to the server. The input is the document file, and the output is the transfer of the document file to the server. The selection and uploading are performed through a React Native application on the smart device.

[0935] Step 2:

[0936] The server uses the Django framework to store the uploaded document in a database. The input is the uploaded document file and its metadata (file name, user ID, upload date and time, etc.), and the output is a record of the document and its metadata in the database. Specifically, the server stores the document data and its metadata in the database.

[0937] Step 3:

[0938] The server analyzes the stored documents using natural language processing technology and extracts important logistics information (product name, quantity, date of receipt, etc.). The input is the document file stored in the database, and the output is the extracted important information. Specifically, the server uses Python and NLTK to analyze the documents and extract the specified information.

[0939] Step 4:

[0940] The server selects an appropriate inventory report template based on the information extracted from the historical database and automatically generates a new business document. The input is the extracted important information and the template database, and the output is the newly generated business document. Specifically, the server embeds the extracted information into the template to create a new document.

[0941] Step 5:

[0942] The server sends the generated business document to the smart device for the user to review and edit. The input is the generated document, and the output is the document modified by the user. Specifically, the user uses a React Native application on the smart device to review the generated document and make any necessary edits.

[0943] Step 6:

[0944] The server automatically notifies the relevant departments of the final version of the document. The input is the final version of the document modified by the user, and the output is the notified relevant departments (e.g., warehouse managers and transportation department staff). Specifically, the server sends the final version of the document to the relevant parties using email or a chat system (e.g., Slack).

[0945] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0946] The present invention relates to a system that enables users to upload various sales-related documents from their terminals, and a server to analyze and process the documents to efficiently create and notify users, and also to a system that combines an emotion engine that recognizes the user's emotions and adjusts the content of the documents. The following describes in detail embodiments of the present invention.

[0947] Upload method

[0948] First, a user selects a document file (e.g., a CP document or a service proposal document) using a terminal and uploads it to the server. The uploaded document is saved on the server, and metadata such as the file name, user ID, and upload date and time are recorded along with it.

[0949] Information extraction method

[0950] The server analyzes the stored documents and uses natural language processing (NLP) techniques to extract important information from within the documents (e.g., product name, features, pricing, target market, etc.).

[0951] Emotion Engine Tools

[0952] The server also incorporates an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's input and actions to determine their emotional state. For example, it recognizes emotions based on the user's keyboard input speed and mouse movements as they review documents, as well as facial expression data obtained from a facial recognition camera.

[0953] Automated document generation methods

[0954] The server then refers to a past database and selects an appropriate document template based on the extracted important information and the user's emotions. The emotional information recognized by the emotion engine is reflected in the document generation process, and templates and wording appropriate to the user's emotions are selected.

[0955] User review and editing options

[0956] The generated document can be viewed by the user on their terminal, and they can edit the content as needed. The editing interface is designed for ease of use.

[0957] Document notification method

[0958] The server automatically notifies the relevant departments (such as the legal department or digital marketing department) of the final edited document via email or chat system, allowing the relevant parties to immediately check the contents of the new document.

[0959] Specific examples

[0960] For example, suppose User B uploads a service proposal document for a new product from their device. The server uses natural language processing technology to extract product features and pricing information from the document. At the same time, the emotion engine analyzes User B's keyboard typing speed and facial expressions and determines that User B is feeling stressed. Based on the extracted information and emotional information, the system selects templates from a past database designed to reduce stress and templates with a high concentration of gentle expressions, and automatically generates a new proposal document. User B can then review and edit the generated document on their device, and the final version can be automatically notified to the legal department and digital marketing department.

[0961] In this way, the present invention significantly improves the efficiency of document creation, enables detailed responses that take into account the user's emotional state, and provides a system that reduces errors and enables rapid information sharing.

[0962] The processing flow will be explained below.

[0963] Step 1:

[0964] The user selects a document file using the terminal and clicks the upload button. The terminal sends the selected document file and the user's ID to the server.

[0965] Step 2:

[0966] The server receives the uploaded document file and saves it in the specified storage. At the same time, the server records metadata such as the file name, user ID, and upload date and time in the database.

[0967] Step 3:

[0968] The server analyzes the stored document files and uses natural language processing (NLP) techniques to extract important information from within the documents (e.g., product name, features, pricing, target market, etc.) using techniques such as text mining and semantic analysis.

[0969] Step 4:

[0970] The emotion engine built into the server recognizes the user's emotions. The emotion engine performs emotion analysis based on the user's input speed, operation patterns, and data from the facial recognition camera. For example, it can read the user's facial expressions (joy, anger, sadness, and happiness) to determine the user's emotional state.

[0971] Step 5:

[0972] The server searches and selects the most appropriate document template from its historical database based on the extracted important information and the user's emotional data. If the emotion engine determines that the user is feeling stressed, it selects a template containing words and designs that have a relaxing effect.

[0973] Step 6:

[0974] The server then embeds the extracted key information into the selected template, creating a new, automatically generated document, placing the extracted information appropriately in placeholders within the template.

[0975] Step 7:

[0976] The server sends the automatically generated document to the user's device, where it can be viewed and edited. The user can view the document on their device and edit the content as necessary. This allows for document editing that is particularly conscious of reducing emotional stress.

[0977] Step 8:

[0978] The user then sends the edited document back to the server from the terminal. The server receives the edited document and saves it as the final version. It then receives a notification that editing is complete.

[0979] Step 9:

[0980] The server automatically notifies the relevant departments (e.g., legal department, digital marketing department) of the final version of the document. Notifications are sent via email or chat system, allowing the relevant parties to immediately check the contents of the new document. Along with notifications, the system also includes a function to report when the user's stress level has been reduced by the emotion engine.

[0981] Step 10:

[0982] The relevant departments will review the final document sent from the server and take any necessary action, completing the entire document creation and notification process.

[0983] Example 2

[0984] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0985] Conventional document creation systems automatically generate documents without taking the user's emotional state into consideration, making it difficult to respond flexibly to the user's mental state. Furthermore, checking and editing documents after generation is cumbersome, making it difficult to provide an efficient work environment. Furthermore, sharing generated documents with related departments is time-consuming, resulting in a lack of speed in information sharing.

[0986] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0987] In this invention, the server includes means for saving documents uploaded from terminals, means for extracting important information from the saved documents using natural language processing technology, means for automatically generating document templates based on the extracted information and referencing a past database, means for recognizing the user's emotional state and reflecting this in the selection of a document template, means for allowing the user to check and edit the automatically generated document, and means for automatically notifying relevant departments of the final document. This enables detailed document generation that takes the user's emotional state into consideration, efficient checking and editing, and rapid information sharing.

[0988] "Terminal" refers to a computer or smart device used by a user to upload documents to this system.

[0989] "Server" means a central computing device that stores and analyzes uploaded documents, and includes hardware and software for performing various system processes.

[0990] "Documents" refer to sales-related documents such as service proposal materials and CP materials, and are files that users upload to the system via their terminals.

[0991] "Natural language processing technology" refers to the technology that allows computers to understand and analyze human language, and is used to extract important information from documents.

[0992] "Important Information" refers to specific items contained within the document, such as product name, features, pricing, target market, etc.

[0993] The "emotion engine" is a system component that analyzes the user's input data and operation information and recognizes the user's emotional state.

[0994] A "template" refers to a format that defines a specific document format and is a framework for embedding extracted important information.

[0995] "Document template selection" is the process of determining an appropriate template based on the user's emotional state and information extracted from a historical database.

[0996] "Verifying and editing" refers to the process in which the user reviews the generated document on the terminal and corrects the content as necessary.

[0997] "Relevant departments" are departments that receive the generated documents, including, for example, the legal department and the digital marketing department.

[0998] "Notification" refers to the process of informing relevant departments of completed documents via email or chat system.

[0999] The present invention relates to a system that enables users to upload various sales-related documents from their terminals, and a server to analyze and process the documents to efficiently create and notify users, and also to a system that combines an emotion engine that recognizes the user's emotions and adjusts the content of the documents. The following describes in detail embodiments of the present invention.

[1000] System Configuration

[1001] Document Upload

[1002] First, a user uses a terminal to select a document file (e.g., a service proposal or CP document) and upload it to the server. The uploaded document is stored on the server, along with metadata such as the file name, user ID, and upload date and time. This upload process uses an HTTP POST request.

[1003] Information extraction using natural language processing

[1004] The server analyzes the uploaded documents and uses natural language processing technology to extract important information from within the documents (e.g., product name, features, pricing, target market, etc.). Specifically, analysis is performed using NLTK (Natural Language Toolkit), a Python natural language processing library. The extracted information is stored in a database for subsequent processing.

[1005] Emotion recognition by emotion engine

[1006] The server also incorporates an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's input and operations to determine their emotional state. Specifically, it uses keyboard input speed and mouse movements as the user reviews a document, as well as facial expression data obtained using OpenCV and facial recognition AI. This allows the server to determine the user's emotional state, such as whether they are feeling stressed.

[1007] Document template selection and auto-generation

[1008] The server selects an appropriate document template by referring to the past database based on the extracted important information and the user's emotional state. It selects a template that reflects the user's emotional state and automatically generates a new document based on that template. MySQL is used for database management.

[1009] User review and editing

[1010] The generated document can be viewed on the user's device and edited as needed. The editing interface is built using JavaScript frameworks such as React and Vue.js, with ease of use in mind.

[1011] Document Notification

[1012] The server automatically notifies the relevant departments, including the legal department and digital marketing department, of the final edited document. Notifications are sent via email or chat systems such as Slack, allowing the relevant parties to immediately view the contents of the new document.

[1013] Specific examples

[1014] For example, suppose User B uploads a service proposal document for a new product from their device. The server extracts product features and pricing information from the document using Python's NLTK. At the same time, the emotion engine uses OpenCV and facial recognition AI to analyze User B's keyboard typing speed and facial expressions and determines that User B is feeling stressed. Based on the extracted information and emotional information, the server selects templates for stress reduction and templates with many softer expressions from a MySQL database and automatically generates new proposal documents. User B can review and edit the generated documents through an editing interface built with React or Vue.js, and the final version can be automatically notified to the legal department and digital marketing department via Slack.

[1015] This system significantly improves the efficiency of document creation, enabling detailed document generation according to the user's emotional state, and streamlines the review and editing process, enabling rapid information sharing.

[1016] Prompt Sentence Examples

[1017] "Please upload a service proposal document for a new product. The system will extract important information from the document and automatically generate a document that takes into account the user's emotional state using an emotion engine. The generated document can be viewed and edited on your device."

[1018] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1019] Step 1:

[1020] The user selects a document file using the terminal and uploads it to the server.

[1021] Input: A document file selected by the user, and an upload button operation.

[1022] Data processing and calculation: The user selects a file through a dedicated interface, and the file and its metadata (file name, user ID, upload date and time) are sent to the server via an HTTP POST request.

[1023] Output: Document files and metadata are saved on the server.

[1024] Specific operation: The user accesses the upload screen, clicks the "Choose File" button to select a document file, and then presses the "Upload" button to send the file to the server.

[1025] Step 2:

[1026] The server analyzes the uploaded documents and extracts key information using natural language processing techniques.

[1027] Input: A document file stored on the server.

[1028] Data processing and calculation: Uses Python's natural language processing library NLTK to extract important information from document content, such as product names, features, pricing, and target markets.

[1029] Output: The extracted important information is stored in a database.

[1030] Specific operation: After receiving the document, the server uses NLTK to analyze the content and extract the necessary information, which is then stored in a database.

[1031] Step 3:

[1032] The server uses an emotion engine to recognize the user's emotional state.

[1033] Input: User keyboard typing speed, mouse movements, and facial expression data.

[1034] Data processing and calculation: OpenCV and facial expression recognition AI are used to analyze this data and determine the user's emotional state.

[1035] Output: User's emotional state information is obtained.

[1036] How it works: The server monitors the user's keyboard input speed and mouse movements, analyzes the user's facial expressions using facial recognition AI, and combines this information to determine the user's emotional state.

[1037] Step 4:

[1038] Based on the information and emotional state extracted by the server, a document template is selected and automatically generated.

[1039] Input: Extracted important information, user emotional state information.

[1040] Data processing and calculation: By referring to the past database, a template suitable for the extracted information and emotional state is selected, and the necessary information is embedded in the template to automatically generate a document.

[1041] Output: Auto-generated documentation.

[1042] Specific operation: The server searches the database, selects an appropriate template, and generates a document by embedding the extracted information in the selected template.

[1043] Step 5:

[1044] The user checks and edits the generated document on the terminal.

[1045] Input: The generated document sent from the server.

[1046] Data processing and calculation: The user checks the document contents and edits them as necessary using the mouse and keyboard.

[1047] Output: The final edited document.

[1048] Specific operation: The user checks the generated document on the device, reviews the content, clicks to select the necessary parts, and makes corrections using the keyboard.

[1049] Step 6:

[1050] The server automatically notifies the relevant departments of the final edited document.

[1051] Input: The final document edited and saved by the user.

[1052] Data processing and calculation: The server sends the final document to the relevant department via email or chat system (e.g., Slack).

[1053] Output: Final document notified to relevant departments.

[1054] Specific operation: When the user completes editing and presses the "Send" button, the server receives the final document and notifies the relevant departments via email or Slack.

[1055] (Application example 2)

[1056] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1057] In conventional document creation systems, users had to manually create, edit, and notify multiple documents, which was a cumbersome process. It was also difficult to create documents that took into account the user's feelings and state, and the fine-tuned wording required to improve the quality of customer service was insufficient. This placed a heavy burden on users and made it difficult to efficiently manage business operations.

[1058] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1059] In this invention, the server includes means for saving documents uploaded from terminals, means for extracting important information from the saved documents, means for automatically generating document templates based on the extracted information and referencing a past database, means for allowing users to check and edit the automatically generated documents, means for automatically notifying relevant departments of the final document, and means for recognizing the user's emotions and adjusting the document content, thereby enabling efficient document creation and rapid information sharing that take the user's emotional state into consideration.

[1060] "Documents uploaded from a terminal" refers to document files transferred from the electronic device used by the user to the server via a network.

[1061] "Storage means" refers to a storage device for holding documents uploaded to a server for a certain period of time, and a method for managing such storage.

[1062] "Means for extracting important information" refers to analytical methods or software that can extract specific important information from the document content.

[1063] A "historical database" refers to data storage that stores documents and related information created in the past.

[1064] "Means for automatically generating document templates" refers to a technology that uses a computer program to automatically create new document templates based on information from past databases.

[1065] "Means for viewing and editing" refers to an interface or software that allows a user to view the contents of the generated document and make corrections or changes as necessary.

[1066] "Means for automatically notifying relevant departments" refers to a system that automatically sends the final generated document to specific departments or personnel via email, chat application, etc.

[1067] "Means for recognizing user emotions and adjusting document content" refers to algorithms or software that analyze the user's emotional state based on input data or biometric information, and change the wording and content of the document accordingly.

[1068] The present invention is a system in which a user uploads various sales-related documents from a terminal, and a server analyzes and processes the documents to efficiently create and notify them. It also includes an emotion engine that recognizes the user's emotions and adjusts the content of the document. Specific embodiments for implementing the present invention are described below.

[1069] Upload and storage methods

[1070] Users use their terminals to select document files such as CP materials or service proposal materials and upload them to the server. The server stores the uploaded documents and records metadata such as the file name, user ID, and upload date and time. The hardware used in this process is the user's PC or smart device, as well as the server's storage device.

[1071] Information extraction method

[1072] The server analyzes the stored documents and extracts key information using natural language processing techniques (e.g., spaCy). This extracted information is used to extract specific keywords and phrases from the document content (e.g., product name, features, pricing, target market, etc.).

[1073] Emotion Engine Tools

[1074] The server is equipped with an emotion engine to recognize the user's emotions by using keystroke speed, mouse movements, and facial expression data obtained from a facial recognition camera (e.g., EmotionRecognizer) as the user reviews the document.

[1075] Automated document generation methods

[1076] The server automatically generates an appropriate document template based on the extracted information and the user's emotions, referencing a past database. The generated document adjusts the wording and expressions to take the user's emotional state into consideration.

[1077] User review and editing options

[1078] The generated document is then made available to the user on their device, where they can edit it as needed through an easy-to-use interface, either using dedicated document editing software or a web application.

[1079] Document notification method

[1080] The server automatically notifies the relevant departments (e.g., legal and marketing) of the final edited document via email or a chat system.

[1081] Specific examples

[1082] For example, consider a virtual store operator who answers customer questions in real time. The operator uses smart glasses or a head-mounted display to quickly generate and present relevant documents in response to the customer's question. In this case, the following prompt sentences are used:

[1083] Prompt example

[1084] I have uploaded the document with the information the customer is requesting:

[1085] Document Content: {Document Content}

[1086] User data: {typing speed, facial expressions, tone of voice}

[1087] Select the appropriate template and provide the generated document.

[1088] Produce effective documentation and emotionally sensitive briefings.

[1089] This system enables efficient document creation and rapid information sharing that takes into account the user's emotional state. It is also expected to improve the quality of customer service in virtual stores and increase user satisfaction.

[1090] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1091] Step 1:

[1092] The user uploads sales-related documents from the terminal.

[1093] Input: Document file (e.g., CP documents, service proposal documents)

[1094] Output: Document file sent to the server

[1095] Specific operation: The user selects a document file using the file selection dialog on the device and clicks the upload button. At that time, metadata such as the file name, user ID, and upload date and time are sent to the server.

[1096] Step 2:

[1097] The server stores the uploaded document file.

[1098] Input: Document files uploaded by users, along with associated metadata

[1099] Output: Document files and metadata stored in the server storage

[1100] Specific operation: The server receives the document file and metadata, saves the file in the specified directory, and stores the metadata in the database.

[1101] Step 3:

[1102] The server uses natural language processing techniques to extract important information from stored documents.

[1103] Input: Saved document file

[1104] Output: Extracted key information (e.g. product name, features, pricing, target market, etc.)

[1105] What it does: The server reads the document file and uses a natural language processing library (e.g., spaCy) to extract keywords and phrases from the document content. The extracted information is temporarily stored in memory.

[1106] Step 4:

[1107] The server activates an emotion engine that recognizes the user's emotions.

[1108] Input: User input data (e.g., keystroke speed, mouse movements, facial expressions, etc.)

[1109] Output: User's emotional state (e.g., stress, joy, concentration, etc.)

[1110] Specific operation: The server inputs the user's keystroke speed, mouse movements, and facial expression data obtained from a face recognition camera into an emotion recognition library (e.g., EmotionRecognizer) to determine the user's emotional state.

[1111] Step 5:

[1112] The server automatically generates a document template by referencing a past database based on the extracted information and the user's emotional state.

[1113] Input: Extracted important information, user's emotional state, historical database

[1114] Output: Auto-generated document template

[1115] Specific operation: The server searches the past database based on the extracted information and emotional state, selects an appropriate document template, embeds the extracted information in the template, and generates a new document.

[1116] Step 6:

[1117] The user reviews and edits the generated document.

[1118] Input: Auto-generated document template

[1119] Output: The final document reviewed and edited by the user

[1120] Specific operation: The user checks the automatically generated document through the editing interface on the terminal and edits the content as necessary. The changes are updated in real time on the server.

[1121] Step 7:

[1122] The server automatically notifies the relevant departments of the final document.

[1123] Input: Final document edited by the user

[1124] Output: Final document notified to relevant departments

[1125] Specific Actions: The server automatically sends the final document to the relevant departments (e.g., legal department, marketing department) via email or chat system, and provides feedback to the user that the notification has been completed.

[1126] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1127] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1128] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1129] [Fourth embodiment]

[1130] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1131] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1132] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1133] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1134] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1135] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1136] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1137] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1138] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1139] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1140] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1141] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1142] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1143] The present invention relates to a system that enables users to upload various sales-related documents from their terminals and a server to analyze and process the documents, thereby achieving efficient document creation and notification. The following describes in detail an embodiment of the present invention.

[1144] Upload method

[1145] First, a user selects a document file (e.g., a CP document or a service proposal document) using a terminal and uploads it to the server. The uploaded document is saved on the server, and metadata such as the file name, user ID, and upload date and time are recorded along with it.

[1146] Information extraction method

[1147] The server analyzes the stored documents and uses natural language processing techniques to extract key information, such as product name, features, pricing, target market, etc.

[1148] Automated document generation methods

[1149] Next, the server selects an appropriate document template based on the extracted important information by referencing the historical database, and automatically generates a new document by embedding the extracted information into the template.

[1150] User review and editing options

[1151] The generated document can be viewed by the user on their device, and they can edit the content as needed. The editing interface is designed for ease of use.

[1152] Document notification method

[1153] The server automatically notifies the relevant departments of the final edited document via email or chat, allowing departments such as the legal department and digital marketing department to instantly view the new document contents.

[1154] Specific examples

[1155] For example, suppose User A uploads a service proposal document for a new product from their device. The server uses natural language processing technology to extract product features and pricing information from the document. Based on the extracted information, the server references proposal document templates from past similar products and automatically generates a new proposal document. User A reviews the generated document on their device and makes any necessary corrections, after which the server automatically notifies the legal department and digital marketing department of the final version.

[1156] In this way, the present invention provides a system that significantly improves the efficiency of document creation, reduces the occurrence of errors, and enables rapid information sharing.

[1157] The processing flow will be explained below.

[1158] Step 1:

[1159] The user selects a document file using the terminal and clicks the upload button. The terminal sends the selected file to the server.

[1160] Step 2:

[1161] The server receives the uploaded document file and saves it in storage. At the same time, the server records metadata such as the file name, user ID, and upload date and time in a database.

[1162] Step 3:

[1163] The server analyzes the stored document files and uses natural language processing (NLP) techniques to extract important information from within the documents (e.g., product name, features, pricing, target market).

[1164] Step 4:

[1165] Based on the extracted key information, the server searches for and selects the most similar document template by referring to a database of past development documents and templates.

[1166] Step 5:

[1167] The server then processes the selected template to embed the extracted important information, resulting in a new, automatically generated document.

[1168] Step 6:

[1169] The server sends the automatically generated document to the user's device, allowing the user to check the document contents. The user can then check the document on their device and edit it as necessary.

[1170] Step 7:

[1171] The user edits the document and sends it to the server, which receives the edits and saves them as the final document.

[1172] Step 8:

[1173] The server automatically notifies the relevant departments (e.g., legal department, digital marketing department) of the final document via email or chat system, allowing the relevant parties to instantly check the document contents.

[1174] Example 1

[1175] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1176] In conventional document creation systems, the processes of document uploading, analysis, generation, editing, and notification are fragmented, resulting in low overall efficiency and delays in information sharing. Furthermore, systems that automate document creation by applying natural language processing and generative AI models are not yet widespread, resulting in a heavy burden on human resources. The present invention aims to solve these issues and significantly improve the efficiency of document creation and notification.

[1177] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1178] In this invention, the server includes means for saving documents uploaded from a terminal, means for extracting important information from the saved documents using natural language processing technology, means for automatically generating a document template based on the extracted information and referring to a past database, means for generating a document based on the extracted information using a generative AI model, means for allowing a user to check and edit the automatically generated document, means for automatically notifying relevant departments of the final document, and means for recording metadata of the saved document. This automates the entire process from document creation to notification, improving overall efficiency and enabling fast and accurate information sharing.

[1179] A "terminal" is an electronic device such as a computer or smartphone that is operated by a user.

[1180] A "server" is a computer system that receives data sent from a terminal via a network and performs various functions such as storage, analysis, processing, and notification.

[1181] A "document" is a collection of information stored in electronic file format, and includes sales-related materials, proposals, and the like.

[1182] "Saving" is the process of storing a document uploaded to a server in storage so that it can be accessed later.

[1183] "Metadata" is additional information associated with a document, including file name, user ID, upload date and time, etc.

[1184] "Natural language processing technology" is a technology that allows computers to understand human language and is used to extract important information from documents.

[1185] "Important Information" is information necessary to understand the significance of the document, such as the product name, features, pricing, target market, etc., contained within the document.

[1186] A "database" is a system that stores multiple data in an organized manner and allows them to be searched and accessed efficiently.

[1187] A "document template" is a model of a document with a standard format and structure, and serves as the basis for creating a new document.

[1188] A "generative AI model" is an artificial intelligence model that uses machine learning and deep learning to automatically generate new documents.

[1189] "Validation" is the process in which a user checks the content of a generated document and considers its accuracy and suitability.

[1190] "Editing" is the process by which a user changes or modifies the content of a generated document.

[1191] "Notification" is the process of informing relevant departments of the final completed document, and is mainly done via email or chat systems.

[1192] "Related departments" are departments responsible for work related to the generated documents, such as the legal department and the digital marketing department.

[1193] MODE FOR CARRYING OUT THE INVENTION

[1194] The present invention relates to a system that enables efficient document creation and notification by allowing users to upload sales-related documents from their terminals and having a server analyze and process the documents. The following describes in detail an embodiment of the present invention.

[1195] Upload method

[1196] First, the user uses the terminal to select a current sales-related document (e.g., CP document or service proposal document) and upload it to the server. In this upload process, the user opens a file selection dialog on the terminal screen and selects the desired document file. Once the document file is selected, the user clicks the "Upload" button to send the document to the server.

[1197] Preservation and metadata recording methods

[1198] The server receives the document file sent from the device and saves the document in a specific directory. At the same time, it records metadata such as the file name, user ID, and upload date and time in a database (e.g., an SQL database). In this step, the server uses an appropriate SQL query to insert the metadata into the database, allowing the document to be easily searched and referenced later.

[1199] Means of Information Extraction

[1200] The server analyzes the stored documents using natural language processing (NLP) technology (e.g., TensorFlow, SpaCy) to extract important information. This important information includes product names, features, pricing, target markets, etc. Specifically, the NLP engine tokenizes the documents and analyzes the meaning of each token. The analysis results are stored in a database as structured data.

[1201] Means of automatic document generation

[1202] Next, the server selects an appropriate document template based on the extracted key information by referencing a historical database (e.g., MongoDB or SQL database). Once a template is selected, the server provides the information to a generative AI model (e.g., OpenAI's GPT-4) to automatically generate a new document. Specifically, the server embeds the information into the template and outputs it as the final document format.

[1203] User review and editing means

[1204] The generated document is displayed on the user's device, where the user can review the content and make edits as necessary. The user can directly modify each field of the document through the web browser interface. After completing the modifications, the user clicks the "Save" button to send the changes to the server.

[1205] Final Document Notification Method

[1206] Once the user has finished editing the document, it is saved back to the server. The server then automatically notifies the relevant departments of the final version of the document. This notification is done by sending email using the SMTP protocol or by sending a chat message using the Slack API. Specifically, the server obtains the notification address and sends an email or chat message.

[1207] Specific examples

[1208] For example, suppose User A uploads a service proposal document for a new product from their device. The server receives the document and uses natural language processing technology to extract product features and pricing information. Based on the extracted information, the server references past proposal document templates for similar products and generates a new proposal document. User A then reviews the generated document on their device and makes any necessary corrections. Finally, the server notifies the legal department and digital marketing department of the completed document.

[1209] Prompt Sentence Examples

[1210] "Generate a service proposal for a new product. Create the proposal using the following information:

[1211] Product Name: Product X

[1212] Features: high speed processing, low power consumption

[1213] Price: 50,000 yen

[1214] Target market: Small and medium-sized businesses

[1215] Please embed this information in your pitch deck template."

[1216] Thus, the present invention automates each step of the document creation process, greatly improving efficiency.

[1217] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1218] Step 1:

[1219] The user selects a document file (e.g., CP materials or service proposal materials) using the terminal and clicks the "Upload" button. This sends the document file selected through the file selection dialog to the server.

[1220] Input: A document file selected by the user

[1221] Output: The document file sent to the server

[1222] Step 2:

[1223] The server saves the received document file in a specific directory. It also records metadata such as the file name, user ID, and upload date and time in a database. For this purpose, it uses an SQL database to store the metadata. The server receives an HTTP POST request and processes the document file and metadata included in the request.

[1224] Input: Document file sent from the device, metadata (file name, user ID, upload date and time)

[1225] Output: Saved document files, metadata recorded in a database

[1226] Step 3:

[1227] The server analyzes the stored documents using natural language processing techniques (e.g., TensorFlow, SpaCy) to extract important information. The server tokenizes the document text and extracts information based on specific patterns or keywords.

[1228] Input: Saved document file

[1229] Output: Extracted key information (product name, features, pricing, target market)

[1230] Step 4:

[1231] Based on the extracted information, the server selects an appropriate document template by referencing a historical database (e.g., MongoDB, SQL database). The server executes a database query to search and retrieve similar historical document templates.

[1232] Input: Extracted important information

[1233] Output: Selected document template

[1234] Step 5:

[1235] The server uses a generative AI model (e.g., OpenAI's GPT-4) to automatically generate new documents. Specifically, it inputs the extracted information as prompts into the generative AI model and embeds the generated document text into a template.

[1236] Input: Selected document template, extracted key information

[1237] Output: Auto-generated document

[1238] Step 6:

[1239] The generated document is displayed on the user's device, where the user can review the content and edit it as necessary. The user can also directly modify the document text through the web browser interface.

[1240] Input: Auto-generated document

[1241] Output: The corrected document

[1242] Step 7:

[1243] Once the user has completed the revisions, the document is saved back to the server, which then automatically notifies the relevant departments of the final version of the document and sends an email or chat message using an SMTP server or Slack API.

[1244] Input: revised document, contact information of relevant departments

[1245] Output: Final document notified to relevant departments

[1246] This series of processes automates and efficiently executes the process from when a user uploads a document to when the server analyzes, generates, and notifies the user.

[1247] (Application example 1)

[1248] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1249] In today's logistics centers, the creation and management of a wide variety of business-related documents is required. However, manual document creation is time-consuming and carries a high risk of errors. Furthermore, delayed sharing of information reduces operational efficiency. There is a need for a method to solve these problems and achieve efficient and accurate document creation and rapid information sharing.

[1250] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1251] In this invention, the server includes means for saving documents uploaded from terminals, means for extracting important information from the saved documents, means for automatically generating document templates by referencing a past database based on the extracted information, means for allowing users to check and edit the automatically generated documents, means for automatically notifying relevant departments of the final documents, means for extracting important logistics information (product name, quantity, date of receipt, etc.) from the documents and automatically generating an appropriate inventory report template if the documents include business-related documents used in the logistics center, and means for allowing users to check and edit the documents generated on their smart devices. This improves the efficiency of business document creation in logistics centers, reduces errors, and enables rapid information sharing.

[1252] A "terminal" is an electronic device such as a computer or smartphone used by a user.

[1253] A "document" is a digital file that consists of text, images, etc.

[1254] "Saving" refers to the act of recording an uploaded document in a storage device within the server.

[1255] "Extraction" is the act of analyzing and extracting important information from within a document.

[1256] "Natural language processing technology" is a technology that allows computers to analyze and understand natural language.

[1257] A "database" is a collection of documents and information that have been stored in the past.

[1258] A "document template" is a pattern that defines the format and structure of a document.

[1259] "Automatic generation" refers to the act of a computer creating a document based on extracted information.

[1260] "Verification" is the act of a user reviewing the generated document.

[1261] "Editing" is an action in which a user modifies the content of a generated document.

[1262] "Notification" is the act of communicating to report the generated document to the relevant department.

[1263] A "logistics center" is a facility that handles logistics operations such as receiving, storing, and shipping goods.

[1264] "Business-related documents" are documents necessary for carrying out daily business.

[1265] A "smart device" is a mobile information terminal with advanced functions, such as a smartphone or tablet.

[1266] An "inventory report" is a document used to record inventory status.

[1267] In the system realizing the present invention, the following elements are used to automatically generate and notify documents.

[1268] Hardware and software used

[1269] 1. Hardware:

[1270] Smart devices (smartphones and tablets)

[1271] server

[1272] 2. Software:

[1273] Python

[1274] Django (server-side framework)

[1275] NLTK (Natural Language Processing Library)

[1276] React Native (application development for smart devices)

[1277] Data processing and calculation

[1278] Upload method

[1279] Users use their smart devices to select business-related documents (e.g., inventory lists and outbound lists) and upload them to the server. The React Native application makes it easy to select and upload files.

[1280] Preservation methods

[1281] Uploaded documents are stored in a database on the server using the Django framework, along with metadata such as file name, user ID, and upload date and time.

[1282] Information extraction method

[1283] The stored documents are analyzed on the server using Python and NLTK, and key logistics information such as product name, quantity, and receipt date is extracted from the documents using natural language processing technology.

[1284] Automated document generation methods

[1285] Based on the extracted information, the server selects an appropriate inventory report template from the historical database, and by filling in the extracted information in the template, a new business document is automatically generated.

[1286] User review and editing options

[1287] The generated documentation is made available for users to view on their smart devices, and users can edit the generated documentation using a React Native application.

[1288] Document notification method

[1289] The server automatically notifies the relevant departments of the final edited version via email or chat system (e.g., Slack), allowing warehouse managers and transportation staff to instantly check the contents of the new document.

[1290] Specific examples

[1291] As an example, consider the case where User B at a logistics center uploads a list of products received that day. The server uses natural language processing technology to extract important information from the list, such as product name, quantity, and receiving date. Next, it automatically generates a new report by filling in an appropriate inventory report template based on the extracted information. User B checks the generated report using a smart device and makes any necessary corrections. The server then automatically notifies the warehouse manager and transportation department staff of the corrected report.

[1292] Prompt Sentence Examples

[1293] "Develop a program to automatically generate inventory reports for a distribution center. Follow these steps:

[1294] 1. Upload business-related documents (stock receipt lists and stock issue lists) from your smart device.

[1295] 2. Extract key information from documents, such as product name, quantity, and receipt date, using natural language processing.

[1296] 3. Based on the extracted information, select an appropriate inventory report template and automatically generate a new document.

[1297] 4. Allow users to view and edit the generated documents on their smart devices.

[1298] 5. Notify the warehouse manager and transportation department staff of the edited document.

[1299] This invention improves the efficiency of business document creation at logistics centers, reduces errors, and enables quick information sharing.

[1300] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1301] Step 1:

[1302] A user uses a smart device to select business-related documents (e.g., inventory receipt list or inventory issue list) and upload them to the server. The input is the document file, and the output is the transfer of the document file to the server. The selection and uploading are performed through a React Native application on the smart device.

[1303] Step 2:

[1304] The server uses the Django framework to store the uploaded document in a database. The input is the uploaded document file and its metadata (file name, user ID, upload date and time, etc.), and the output is a record of the document and its metadata in the database. Specifically, the server stores the document data and its metadata in the database.

[1305] Step 3:

[1306] The server analyzes the stored documents using natural language processing technology and extracts important logistics information (product name, quantity, date of receipt, etc.). The input is the document file stored in the database, and the output is the extracted important information. Specifically, the server uses Python and NLTK to analyze the documents and extract the specified information.

[1307] Step 4:

[1308] The server selects an appropriate inventory report template based on the information extracted from the historical database and automatically generates a new business document. The input is the extracted important information and the template database, and the output is the newly generated business document. Specifically, the server embeds the extracted information into the template to create a new document.

[1309] Step 5:

[1310] The server sends the generated business document to the smart device for the user to review and edit. The input is the generated document, and the output is the document modified by the user. Specifically, the user uses a React Native application on the smart device to review the generated document and make any necessary edits.

[1311] Step 6:

[1312] The server automatically notifies the relevant departments of the final version of the document. The input is the final version of the document modified by the user, and the output is the notified relevant departments (e.g., warehouse managers and transportation department staff). Specifically, the server sends the final version of the document to the relevant parties using email or a chat system (e.g., Slack).

[1313] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1314] The present invention relates to a system that enables users to upload various sales-related documents from their terminals, and a server to analyze and process the documents to efficiently create and notify users, and also to a system that combines an emotion engine that recognizes the user's emotions and adjusts the content of the documents. The following describes in detail embodiments of the present invention.

[1315] Upload method

[1316] First, a user selects a document file (e.g., a CP document or a service proposal document) using a terminal and uploads it to the server. The uploaded document is saved on the server, and metadata such as the file name, user ID, and upload date and time are recorded along with it.

[1317] Information extraction method

[1318] The server analyzes the stored documents and uses natural language processing (NLP) techniques to extract important information from within the documents (e.g., product name, features, pricing, target market, etc.).

[1319] Emotion Engine Tools

[1320] The server also incorporates an emotion engine that recognizes the user's emotions. This emotion engine analyzes the user's input and actions to determine their emotional state. For example, it recognizes emotions based on the user's keyboard input speed and mouse movements as they review documents, as well as facial expression data obtained from a facial recognition camera.

[1321] Automated document generation methods

[1322] The server then refers to a past database and selects an appropriate document template based on the extracted important information and the user's emotions. The emotional information recognized by the emotion engine is reflected in the document generation process, and templates and wording appropriate to the user's emotions are selected.

[1323] User review and editing options

[1324] The generated document can be viewed by the user on their terminal, and they can edit the content as needed. The editing interface is designed for ease of use.

[1325] Document notification method

[1326] The server automatically notifies the relevant departments (such as the legal department or digital marketing department) of the final edited document via email or chat system, allowing the relevant parties to immediately check the contents of the new document.

[1327] Specific examples

[1328] For example, suppose User B uploads a service proposal document for a new product from their device. The server uses natural language processing technology to extract product features and pricing information from the document. At the same time, the emotion engine analyzes User B's keyboard typing speed and facial expressions and determines that User B is feeling stressed. Based on the extracted information and emotional information, the system selects templates from a past database designed to reduce stress and templates with a high concentration of gentle expressions, and automatically generates a new proposal document. User B can then review and edit the generated document on their device, and the final version can be automatically notified to the legal department and digital marketing department.

[1329] In this way, the present invention significantly improves the efficiency of document creation, enables detailed responses that take into account the user's emotional state, and provides a system that reduces errors and enables rapid information sharing.

[1330] The processing flow will be explained below.

[1331] Step 1:

[1332] The user selects a document file using the terminal and clicks the upload button. The terminal sends the selected document file and the user's ID to the server.

[1333] Step 2:

[1334] The server receives the uploaded document file and saves it in the specified storage. At the same time, the server records metadata such as the file name, user ID, and upload date and time in the database.

[1335] Step 3:

[1336] The server analyzes the stored document files and uses natural language processing (NLP) techniques to extract important information from within the documents (e.g., product name, features, pricing, target market, etc.) using techniques such as text mining and semantic analysis.

[1337] Step 4:

[1338] The emotion engine built into the server recognizes the user's emotions. The emotion engine performs emotion analysis based on the user's input speed, operation patterns, and data from the facial recognition camera. For example, it can read the user's facial expressions (joy, anger, sadness, and happiness) to determine the user's emotional state.

[1339] Step 5:

[1340] The server searches and selects the most appropriate document template from its historical database based on the extracted important information and the user's emotional data. If the emotion engine determines that the user is feeling stressed, it selects a template containing words and designs that have a relaxing effect.

[1341] Step 6:

[1342] The server then embeds the extracted key information into the selected template, creating a new, automatically generated document, placing the extracted information appropriately in placeholders within the template.

[1343] Step 7:

[1344] The server sends the automatically generated document to the user's device, where it can be viewed and edited. The user can view the document on their device and edit the content as necessary. This allows for document editing that is particularly conscious of reducing emotional stress.

[1345] Step 8:

[1346] The user then sends the edited document back to the server from the terminal. The server receives the edited document and saves it as the final version. It then receives a notification that editing is complete.

[1347] Step 9:

[1348] The server automatically notifies the relevant departments (e.g., legal department, digital marketing department) of the final version of the document. Notifications are sent via email or chat system, allowing the relevant parties to immediately check the contents of the new document. Along with notifications, the system also includes a function to report when the user's stress level has been reduced by the emotion engine.

[1349] Step 10:

[1350] The relevant departments will review the final document sent from the server and take any necessary action, completing the entire document creation and notification process.

[1351] Example 2

[1352] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1353] Conventional document creation systems automatically generate documents without taking the user's emotional state into consideration, making it difficult to respond flexibly to the user's mental state. Furthermore, checking and editing documents after generation is cumbersome, making it difficult to provide an efficient work environment. Furthermore, sharing generated documents with related departments is time-consuming, resulting in a lack of speed in information sharing.

[1354] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1355] In this invention, the server includes means for saving documents uploaded from terminals, means for extracting important information from the saved documents using natural language processing technology, means for automatically generating document templates based on the extracted information and referencing a past database, means for recognizing the user's emotional state and reflecting this in the selection of a document template, means for allowing the user to check and edit the automatically generated document, and means for automatically notifying relevant departments of the final document. This enables detailed document generation that takes the user's emotional state into consideration, efficient checking and editing, and rapid information sharing.

[1356] "Terminal" refers to a computer or smart device used by a user to upload documents to this system.

[1357] "Server" means a central computing device that stores and analyzes uploaded documents, and includes hardware and software for performing various system processes.

[1358] "Documents" refer to sales-related documents such as service proposal materials and CP materials, and are files that users upload to the system via their terminals.

[1359] "Natural language processing technology" refers to the technology that allows computers to understand and analyze human language, and is used to extract important information from documents.

[1360] "Important Information" refers to specific items contained within the document, such as product name, features, pricing, target market, etc.

[1361] The "emotion engine" is a system component that analyzes the user's input data and operation information and recognizes the user's emotional state.

[1362] A "template" refers to a format that defines a specific document format and is a framework for embedding extracted important information.

[1363] "Document template selection" is the process of determining an appropriate template based on the user's emotional state and information extracted from a historical database.

[1364] "Verifying and editing" refers to the process in which the user reviews the generated document on the terminal and corrects the content as necessary.

[1365] "Relevant departments" are departments that receive the generated documents, including, for example, the legal department and the digital marketing department.

[1366] "Notification" refers to the process of informing relevant departments of completed documents via email or chat system.

[1367] The present invention relates to a system that enables users to upload various sales-related documents from their terminals, and a server to analyze and process the documents to efficiently create and notify users, and also to a system that combines an emotion engine that recognizes the user's emotions and adjusts the content of the documents. The following describes in detail embodiments of the present invention.

[1368] System Configuration

[1369] Document Upload

[1370] First, a user uses a terminal to select a document file (e.g., a service proposal or CP document) and upload it to the server. The uploaded document is stored on the server, along with metadata such as the file name, user ID, and upload date and time. This upload process uses an HTTP POST request.

[1371] Information extraction using natural language processing

[1372] The server analyzes the uploaded documents and uses natural language processing technology to extract important information from within the documents (e.g., product name, features, pricing, target market, etc.). Specifically, analysis is performed using NLTK (Natural Language Toolkit), a Python natural language processing library. The extracted information is stored in a database for subsequent processing.

[1373] Emotion recognition by emotion engine

[1374] The server also incorporates an emotion engine that recognizes the user's emotions. The emotion engine analyzes the user's input and operations to determine their emotional state. Specifically, it uses keyboard input speed and mouse movements as the user reviews a document, as well as facial expression data obtained using OpenCV and facial recognition AI. This allows the server to determine the user's emotional state, such as whether they are feeling stressed.

[1375] Document template selection and auto-generation

[1376] The server selects an appropriate document template by referring to the past database based on the extracted important information and the user's emotional state. It selects a template that reflects the user's emotional state and automatically generates a new document based on that template. MySQL is used for database management.

[1377] User review and editing

[1378] The generated document can be viewed on the user's device and edited as needed. The editing interface is built using JavaScript frameworks such as React and Vue.js, with ease of use in mind.

[1379] Document Notification

[1380] The server automatically notifies the relevant departments, including the legal department and digital marketing department, of the final edited document. Notifications are sent via email or chat systems such as Slack, allowing the relevant parties to immediately view the contents of the new document.

[1381] Specific examples

[1382] For example, suppose User B uploads a service proposal document for a new product from their device. The server extracts product features and pricing information from the document using Python's NLTK. At the same time, the emotion engine uses OpenCV and facial recognition AI to analyze User B's keyboard typing speed and facial expressions and determines that User B is feeling stressed. Based on the extracted information and emotional information, the server selects templates for stress reduction and templates with many softer expressions from a MySQL database and automatically generates new proposal documents. User B can review and edit the generated documents through an editing interface built with React or Vue.js, and the final version can be automatically notified to the legal department and digital marketing department via Slack.

[1383] This system significantly improves the efficiency of document creation, enabling detailed document generation according to the user's emotional state, and streamlines the review and editing process, enabling rapid information sharing.

[1384] Prompt Sentence Examples

[1385] "Please upload a service proposal document for a new product. The system will extract important information from the document and automatically generate a document that takes into account the user's emotional state using an emotion engine. The generated document can be viewed and edited on your device."

[1386] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1387] Step 1:

[1388] The user selects a document file using the terminal and uploads it to the server.

[1389] Input: A document file selected by the user, and an upload button operation.

[1390] Data processing and calculation: The user selects a file through a dedicated interface, and the file and its metadata (file name, user ID, upload date and time) are sent to the server via an HTTP POST request.

[1391] Output: Document files and metadata are saved on the server.

[1392] Specific operation: The user accesses the upload screen, clicks the "Choose File" button to select a document file, and then presses the "Upload" button to send the file to the server.

[1393] Step 2:

[1394] The server analyzes the uploaded documents and extracts key information using natural language processing techniques.

[1395] Input: A document file stored on the server.

[1396] Data processing and calculation: Uses Python's natural language processing library NLTK to extract important information from document content, such as product names, features, pricing, and target markets.

[1397] Output: The extracted important information is stored in a database.

[1398] Specific operation: After receiving the document, the server uses NLTK to analyze the content and extract the necessary information, which is then stored in a database.

[1399] Step 3:

[1400] The server uses an emotion engine to recognize the user's emotional state.

[1401] Input: User keyboard typing speed, mouse movements, and facial expression data.

[1402] Data processing and calculation: OpenCV and facial expression recognition AI are used to analyze this data and determine the user's emotional state.

[1403] Output: User's emotional state information is obtained.

[1404] How it works: The server monitors the user's keyboard input speed and mouse movements, analyzes the user's facial expressions using facial recognition AI, and combines this information to determine the user's emotional state.

[1405] Step 4:

[1406] Based on the information and emotional state extracted by the server, a document template is selected and automatically generated.

[1407] Input: Extracted important information, user emotional state information.

[1408] Data processing and calculation: By referring to the past database, a template suitable for the extracted information and emotional state is selected, and the necessary information is embedded in the template to automatically generate a document.

[1409] Output: Auto-generated documentation.

[1410] Specific operation: The server searches the database, selects an appropriate template, and generates a document by embedding the extracted information in the selected template.

[1411] Step 5:

[1412] The user checks and edits the generated document on the terminal.

[1413] Input: The generated document sent from the server.

[1414] Data processing and calculation: The user checks the document contents and edits them as necessary using the mouse and keyboard.

[1415] Output: The final edited document.

[1416] Specific operation: The user checks the generated document on the device, reviews the content, clicks to select the necessary parts, and makes corrections using the keyboard.

[1417] Step 6:

[1418] The server automatically notifies the relevant departments of the final edited document.

[1419] Input: The final document edited and saved by the user.

[1420] Data processing and calculation: The server sends the final document to the relevant department via email or chat system (e.g., Slack).

[1421] Output: Final document notified to relevant departments.

[1422] Specific operation: When the user completes editing and presses the "Send" button, the server receives the final document and notifies the relevant departments via email or Slack.

[1423] (Application example 2)

[1424] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1425] In conventional document creation systems, users had to manually create, edit, and notify multiple documents, which was a cumbersome process. It was also difficult to create documents that took into account the user's feelings and state, and the fine-tuned wording required to improve the quality of customer service was insufficient. This placed a heavy burden on users and made it difficult to efficiently manage business operations.

[1426] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1427] In this invention, the server includes means for saving documents uploaded from terminals, means for extracting important information from the saved documents, means for automatically generating document templates based on the extracted information and referencing a past database, means for allowing users to check and edit the automatically generated documents, means for automatically notifying relevant departments of the final document, and means for recognizing the user's emotions and adjusting the document content, thereby enabling efficient document creation and rapid information sharing that take the user's emotional state into consideration.

[1428] "Documents uploaded from a terminal" refers to document files transferred from the electronic device used by the user to the server via a network.

[1429] "Storage means" refers to a storage device for holding documents uploaded to a server for a certain period of time, and a method for managing such storage.

[1430] "Means for extracting important information" refers to analytical methods or software that can extract specific important information from the document content.

[1431] A "historical database" refers to data storage that stores documents and related information created in the past.

[1432] "Means for automatically generating document templates" refers to a technology that uses a computer program to automatically create new document templates based on information from past databases.

[1433] "Means for viewing and editing" refers to an interface or software that allows a user to view the contents of the generated document and make corrections or changes as necessary.

[1434] "Means for automatically notifying relevant departments" refers to a system that automatically sends the final generated document to specific departments or personnel via email, chat application, etc.

[1435] "Means for recognizing user emotions and adjusting document content" refers to algorithms or software that analyze the user's emotional state based on input data or biometric information, and change the wording and content of the document accordingly.

[1436] The present invention is a system in which a user uploads various sales-related documents from a terminal, and a server analyzes and processes the documents to efficiently create and notify them. It also includes an emotion engine that recognizes the user's emotions and adjusts the content of the document. Specific embodiments for implementing the present invention are described below.

[1437] Upload and storage methods

[1438] Users use their terminals to select document files such as CP materials or service proposal materials and upload them to the server. The server stores the uploaded documents and records metadata such as the file name, user ID, and upload date and time. The hardware used in this process is the user's PC or smart device, as well as the server's storage device.

[1439] Information extraction method

[1440] The server analyzes the stored documents and extracts key information using natural language processing techniques (e.g., spaCy). This extracted information is used to extract specific keywords and phrases from the document content (e.g., product name, features, pricing, target market, etc.).

[1441] Emotion Engine Tools

[1442] The server is equipped with an emotion engine to recognize the user's emotions by using keystroke speed, mouse movements, and facial expression data obtained from a facial recognition camera (e.g., EmotionRecognizer) as the user reviews the document.

[1443] Automated document generation methods

[1444] The server automatically generates an appropriate document template based on the extracted information and the user's emotions, referencing a past database. The generated document adjusts the wording and expressions to take the user's emotional state into consideration.

[1445] User review and editing options

[1446] The generated document is then made available to the user on their device, where they can edit it as needed through an easy-to-use interface, either using dedicated document editing software or a web application.

[1447] Document notification method

[1448] The server automatically notifies the relevant departments (e.g., legal and marketing) of the final edited document via email or a chat system.

[1449] Specific examples

[1450] For example, consider a virtual store operator who answers customer questions in real time. The operator uses smart glasses or a head-mounted display to quickly generate and present relevant documents in response to the customer's question. In this case, the following prompt sentences are used:

[1451] Prompt example

[1452] I have uploaded the document with the information the customer is requesting:

[1453] Document Content: {Document Content}

[1454] User data: {typing speed, facial expressions, tone of voice}

[1455] Select the appropriate template and provide the generated document.

[1456] Produce effective documentation and emotionally sensitive briefings.

[1457] This system enables efficient document creation and rapid information sharing that takes into account the user's emotional state. It is also expected to improve the quality of customer service in virtual stores and increase user satisfaction.

[1458] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1459] Step 1:

[1460] The user uploads sales-related documents from the terminal.

[1461] Input: Document file (e.g., CP documents, service proposal documents)

[1462] Output: Document file sent to the server

[1463] Specific operation: The user selects a document file using the file selection dialog on the device and clicks the upload button. At that time, metadata such as the file name, user ID, and upload date and time are sent to the server.

[1464] Step 2:

[1465] The server stores the uploaded document file.

[1466] Input: Document files uploaded by users, along with associated metadata

[1467] Output: Document files and metadata stored in the server storage

[1468] Specific operation: The server receives the document file and metadata, saves the file in the specified directory, and stores the metadata in the database.

[1469] Step 3:

[1470] The server uses natural language processing techniques to extract important information from stored documents.

[1471] Input: Saved document file

[1472] Output: Extracted key information (e.g. product name, features, pricing, target market, etc.)

[1473] What it does: The server reads the document file and uses a natural language processing library (e.g., spaCy) to extract keywords and phrases from the document content. The extracted information is temporarily stored in memory.

[1474] Step 4:

[1475] The server activates an emotion engine that recognizes the user's emotions.

[1476] Input: User input data (e.g., keystroke speed, mouse movements, facial expressions, etc.)

[1477] Output: User's emotional state (e.g., stress, joy, concentration, etc.)

[1478] Specific operation: The server inputs the user's keystroke speed, mouse movements, and facial expression data obtained from a face recognition camera into an emotion recognition library (e.g., EmotionRecognizer) to determine the user's emotional state.

[1479] Step 5:

[1480] The server automatically generates a document template by referencing a past database based on the extracted information and the user's emotional state.

[1481] Input: Extracted important information, user's emotional state, historical database

[1482] Output: Auto-generated document template

[1483] Specific operation: The server searches the past database based on the extracted information and emotional state, selects an appropriate document template, embeds the extracted information in the template, and generates a new document.

[1484] Step 6:

[1485] The user reviews and edits the generated document.

[1486] Input: Auto-generated document template

[1487] Output: The final document reviewed and edited by the user

[1488] Specific operation: The user checks the automatically generated document through the editing interface on the terminal and edits the content as necessary. The changes are updated in real time on the server.

[1489] Step 7:

[1490] The server automatically notifies the relevant departments of the final document.

[1491] Input: Final document edited by the user

[1492] Output: Final document notified to relevant departments

[1493] Specific Actions: The server automatically sends the final document to the relevant departments (e.g., legal department, marketing department) via email or chat system, and provides feedback to the user that the notification has been completed.

[1494] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1495] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1496] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1497] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1498] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1499] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1500] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1501] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1502] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1503] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1504] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1505] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1506] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1507] 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.

[1508] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1509] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1510] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1511] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1512] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1513] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1514] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1515] The following is further disclosed regarding the above embodiment.

[1516] (Claim 1)

[1517] a means for storing documents uploaded from the device;

[1518] a means for extracting important information from the stored documents;

[1519] A means for automatically generating a document template by referencing a past database based on the extracted information;

[1520] A means for users to review and edit the automatically generated documents;

[1521] A means of automatically notifying the relevant departments of the final document;

[1522] A system including:

[1523] (Claim 2)

[1524] 10. The system of claim 1, further comprising means for selecting a template that is similar to the information extracted from the historical database.

[1525] (Claim 3)

[1526] 10. The system of claim 1, further comprising means for extracting significant information from the document using natural language processing techniques.

[1527] "Example 1"

[1528] (Claim 1)

[1529] a means for storing documents uploaded from the device;

[1530] A means for extracting important information from stored documents using natural language processing techniques;

[1531] A means for automatically generating a document template by referencing a past database based on the extracted information;

[1532] A means for users to review and edit the automatically generated documents;

[1533] A means of automatically notifying the relevant departments of the final document;

[1534] a means for generating a document based on the extracted information using a generative AI model;

[1535] A system including:

[1536] (Claim 2)

[1537] 10. The system of claim 1, further comprising means for selecting a template that is similar to the information extracted from the historical database.

[1538] (Claim 3)

[1539] 10. The system of claim 1, further comprising: means for recording metadata of the stored document.

[1540] "Application Example 1"

[1541] (Claim 1)

[1542] a means for storing documents uploaded from the device;

[1543] a means for extracting important information from the stored documents;

[1544] A means for automatically generating a document template by referencing a past database based on the extracted information;

[1545] A means for users to review and edit the automatically generated documents;

[1546] A means of automatically notifying the relevant departments of the final document;

[1547] When documents include business-related documents used in a logistics center, a means for extracting important logistics information (product name, quantity, date of receipt, etc.) from the documents and automatically generating an inventory report based on an appropriate inventory report template;

[1548] A means by which users can review and edit the generated documents on their smart devices;

[1549] A system including:

[1550] (Claim 2)

[1551] 10. The system of claim 1, further comprising means for selecting a template that is similar to the information extracted from the historical database.

[1552] (Claim 3)

[1553] 10. The system of claim 1, further comprising means for extracting significant information from the document using natural language processing techniques.

[1554] "Example 2: Combining Emotion Engines"

[1555] (Claim 1)

[1556] a means for storing documents uploaded from the device;

[1557] means for extracting important information from stored documents using natural language processing techniques;

[1558] A means for automatically generating a document template by referencing a past database based on the extracted information;

[1559] means for recognizing a user's emotional state and reflecting it in the selection of a document template;

[1560] A means for users to review and edit the automatically generated documents;

[1561] A means of automatically notifying the relevant departments of the final document;

[1562] A system including:

[1563] (Claim 2)

[1564] 10. The system of claim 1, further comprising means for selecting an appropriate template based on emotional state and information extracted from a historical database.

[1565] (Claim 3)

[1566] 10. The system of claim 1, further comprising emotion engine means for analyzing input data and operation information of a user to recognize emotions.

[1567] "Application example 2 when combining emotion engines"

[1568] (Claim 1)

[1569] a means for storing documents uploaded from the device;

[1570] a means for extracting important information from the stored documents;

[1571] A means for automatically generating a document template by referencing a past database based on the extracted information;

[1572] A means for users to review and edit the automatically generated documents;

[1573] A means of automatically notifying the relevant departments of the final document;

[1574] means for recognizing a user's emotions and adjusting the document content;

[1575] A system including:

[1576] (Claim 2)

[1577] 10. The system of claim 1, further comprising means for selecting a template that is similar to the information extracted from the historical database.

[1578] (Claim 3)

[1579] 10. The system of claim 1, further comprising means for extracting significant information from the document using natural language processing techniques. [Explanation of symbols]

[1580] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for storing documents uploaded from the device; a means for extracting important information from the stored documents; A means for automatically generating a document template by referencing a past database based on the extracted information; A means for users to review and edit the automatically generated documents; A means of automatically notifying the relevant departments of the final document; A system including:

2. The system of claim 1 further comprising means for selecting templates similar to information extracted from the historical database.

3. The system of claim 1 further comprising means for extracting important information from the document using natural language processing techniques.

Images