System

Abstract

A system is provided.SOLUTION: The system includes a means for allowing a user to input the configuration and detailed contents of a proposed document, a means for retrieving and acquiring related materials from storage services, a means for analyzing the acquired materials by using a generation AI model and extracting main points, a means for automatically generating a presentation file on the basis of the extracted main points, and a means for notifying the user of the link of the generated presentation file.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Proposal preparation involves a wide range of tasks, such as collecting, organizing, and summarizing materials, and requires a great deal of time and effort. Furthermore, much time is often spent searching for the appropriate materials, so efficiency is essential. In particular, in the service industry, it is important to prepare proposals quickly and with high quality, and a method for achieving this efficiently is needed. [Means for solving the problem]

[0005] The system of the present invention includes a means for a user to input the structure and detailed contents of a proposal, a means for searching and retrieving related materials from a storage service, a means for analyzing the retrieved materials using a generative AI model to extract key points, a means for automatically generating a presentation file based on the extracted key points, and a means for notifying the user of a link to the generated presentation file. This automates the process from collecting materials to generating the presentation, reducing the burden on the user and enabling efficient proposal creation.

[0006] "User" means an individual or member of an organization who uses the System to create proposals.

[0007] A "proposal" is a document that describes and proposes a particular service, product, or initiative.

[0008] "Structure" refers to the sections and chapters that make up the proposal, and the predetermined format and order.

[0009] "Detailed content" refers to specific information and explanations included in the proposal, such as an outline of the service, strategy, and budget.

[0010] "Means" refers to the equipment, software, or process used by the system to achieve the relevant function.

[0011] A "storage service" is a service that manages and provides digital data stored in the cloud, local servers, etc.

[0012] "Materials" means documents, reports, data files, and other information sources stored in the Storage Service.

[0013] A "generative AI model" refers to a computer program or algorithm that uses artificial intelligence to analyze and generate text.

[0014] "Key points" are the main information or important points extracted from the material.

[0015] A "presentation file" is a digital file in slide format used to visually represent the contents of a proposal.

[0016] "Link" means a URL or hyperlink that provides direct access to a particular file or resource.

[0017] "Authentication" means a process or tool that verifies a user's identity and allows or denies access to a system.

[0018] A "dashboard" is an administration screen or operation screen that is displayed after a user logs in to the system.

[0019] "Presentation creation software" is application software for creating slide-format presentation files. [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] This invention is a system that automatically creates proposals by collecting related materials from storage services when a user inputs the structure and content of the proposal. This system is composed of multiple means, each of which works together to efficiently generate proposals.

[0042] A natural language explanation of the program's processing

[0043] 1. User Input Processing

[0044] First, the user logs in to the system from their terminal. The terminal sends the user's login information (user name and password) to the server, and the server authenticates the user using an authentication method. If authentication is successful, the user is redirected to their dashboard. Next, the user enters the proposal structure and detailed service content to create a new proposal. The terminal then sends this information to the server.

[0045] 2. Information Collection and Processing

[0046] The server uses the storage service's API to search for relevant materials based on the keywords and content structure entered by the user. The storage service returns a list of relevant files to the server as search results. The server receives the list and downloads the necessary files.

[0047] 3. Data analysis and processing

[0048] The downloaded materials are provided to the generative AI model, which is then run by the server to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. This extracted information is then organized by the server based on the proposal structure.

[0049] 4. Presentation Generation Process

[0050] Next, the server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which automatically generates slides corresponding to each section. The generated slides are saved as a single presentation file. The server then checks the location where the completed presentation file is saved and notifies the user of the access link.

[0051] 5. User Notification and Confirmation

[0052] Finally, the server sends a link to the generated presentation file to the device. The user accesses the provided link on the device and checks the generated proposal. If necessary, the user can make corrections to the presentation on the device and check the final proposal. In this way, a high-quality proposal is completed efficiently.

[0053] Specific examples

[0054] As a concrete example, consider a marketer working at an advertising agency creating a proposal for a new social media marketing campaign. The user logs in and starts creating a new proposal. The user enters details such as a service overview, target market, strategy, and budget. The server collects past success stories and marketing reports from a storage service, and a generative AI model summarizes the key points. The automatically generated presentation file is notified to the user, who can review it via a link, make any necessary revisions, and then submit it to the client.

[0055] This system allows for the efficient and rapid creation of high-quality proposals, significantly reducing the time and effort required for proposal work.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] A user logs in to the system from a terminal. The user enters a username and password on the login screen and presses the send button. The terminal sends this information to the server.

[0059] Step 2:

[0060] The server compares the received user information with the database and performs authentication. If authentication is successful, the server sends an instruction to the device to redirect to the user's dashboard.

[0061] Step 3:

[0062] The user clicks the "Create a new proposal" button on the dashboard, which opens a form on the device for entering the proposal structure and service details.

[0063] Step 4:

[0064] The user enters the proposal structure (e.g., objectives, target market, strategy, budget) and detailed service content. After the user has entered all the items, he / she presses the send button. The terminal sends the input information to the server.

[0065] Step 5:

[0066] The server analyzes the received user input information and calls the storage service API to send a request to search for related materials.

[0067] Step 6:

[0068] The storage service returns a list of related files to the server, which then receives the list and downloads the necessary files.

[0069] Step 7:

[0070] The server provides the downloaded materials to the generative AI model, which then analyzes the materials and extracts key points and important information.

[0071] Step 8:

[0072] The generative AI model returns the extracted information to the server, which organizes it into sections of the proposal and determines the slide summaries for each section.

[0073] Step 9:

[0074] The server starts the presentation creation software, instructs it to create a new presentation file, and sends specific summaries for each slide to the presentation creation software.

[0075] Step 10:

[0076] The presentation software automatically generates slides and saves the completed slides as a single presentation file. The server confirms the location and link of the generated presentation file.

[0077] Step 11:

[0078] The server notifies the device of the link to the generated presentation file, and the device displays the notification to the user, who can click the link to view the generated proposal.

[0079] Step 12:

[0080] The user accesses the provided link on their device to view the generated proposal, revise the presentation content as needed, and review the final proposal.

[0081] This allows users to create high-quality proposals quickly and efficiently.

[0082] Example 1

[0083] 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."

[0084] The traditional proposal creation process was highly inefficient, requiring users to spend a significant amount of time gathering information, manually organizing documents, and then creating the final proposal. This also created a risk of missing important information, leading to inconsistent proposal quality. Furthermore, the process of standardizing documents in different formats was time-consuming and burdensome for users.

[0085] 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.

[0086] In this invention, the server includes means for a user to input the structure and detailed contents of a proposal, means for searching and retrieving related materials from a data storage device, means for analyzing the retrieved materials using an artificial intelligence model to extract key points, means for automatically generating a presentation material file based on the extracted key points, means for notifying the user of a link to the generated presentation material file, and means for the user to check the generated proposal via the link and make corrections as necessary. This enables users to efficiently and quickly create high-quality proposals, significantly reducing the time and effort required for proposal work.

[0087] "User" refers to a person who operates the system and creates and checks proposals.

[0088] A "data storage device" is a device or system for storing and managing data, such as a cloud service or server.

[0089] An "artificial intelligence model" is a set of algorithms, such as machine learning models or natural language processing models, used to analyze data and extract key points.

[0090] A "presentation materials file" is a presentation-style file that summarizes the contents of the proposal.

[0091] "Link" is the URL or shared path that users can access to view the generated presentation file.

[0092] "Authentication methods" are technologies and methods for verifying a user's identity and granting legitimate access rights.

[0093] The "user dashboard" is an operation screen that users can access after logging in to the system, and is an interface where they can create and manage proposals.

[0094] "Presentation material creation software" refers to software or tools for creating, editing, and saving presentation files.

[0095] "Notification means" refers to the means by which the system notifies the user of information and file access links.

[0096] This system allows users to input the structure and content of a proposal, and then collects related materials from a data storage device and automatically creates a presentation file.The system includes multiple means, each of which works together to efficiently generate a proposal.

[0097] First, a user accesses the system from a terminal and needs to enter their username and password on the login screen. The terminal sends this login information to the server. The server authenticates the user using an authentication method (e.g., OAuth 2.0) and, if authentication is successful, redirects the user to the dashboard. There, the user can enter the proposal structure and details to create a new proposal.

[0098] The information entered by the user is sent from the device to the server. The server uses a data storage device (e.g., a cloud storage service API, such as Google Drive API or Dropbox API) to search for and retrieve relevant materials. The server then downloads the retrieved materials.

[0099] The server then provides the acquired materials to an artificial intelligence model (e.g., the generative AI model "OpenAI GPT-4") to analyze the materials. The generative AI model analyzes the materials and extracts key points. This extracted information is then organized by the server based on the proposal structure.

[0100] Based on the organized information, the server launches presentation creation software (e.g., Microsoft PowerPoint API or Google Slides API) to create a new presentation file. The extracted key points are automatically generated as slides corresponding to each section and saved as a single presentation file. The server then generates a link to the saved presentation file and notifies the user of the link.

[0101] The user can access the link provided by the server from their device to check the generated proposal. If some edits are required, the user can modify the presentation file from their device and then check and submit the final proposal.

[0102] Here are some concrete examples of how this system can be used:

[0103] When a marketer working at an advertising agency wants to create a proposal for a new social media marketing campaign, the user logs in and clicks the "Create a New Proposal" button on their dashboard. They then enter detailed information such as a service overview, target market, strategy, and budget. The server uses the Google Drive API to collect past success stories and marketing reports, and a generative AI model (OpenAI GPT-4) extracts the key points. The user is then notified of a presentation file automatically generated using the Microsoft PowerPoint API. The user clicks the link to review the file, make any necessary revisions, and submit the final proposal to the client.

[0104] Examples of prompts include:

[0105] "Using the following materials, please write a proposal for a new social media marketing campaign. Include a description of your services, your target market, your strategy, and your budget."

[0106] By inputting this prompt sentence, the generative AI model can generate appropriate suggestions.

[0107] The above is an embodiment of this system.

[0108] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0109] Step 1:

[0110] User login process

[0111] A user accesses the system from a terminal and enters a username and password on the login screen. The terminal sends the entered login information to the server. The server verifies the received login information using an authentication method (e.g., OAuth 2.0). If authentication is successful, the server returns a redirect link to the user's dashboard to the terminal. In this step, the username and password are taken as input, and a dashboard link is generated as output.

[0112] Step 2:

[0113] Proposal content input processing

[0114] The user clicks the "Create a new proposal" button from the dashboard. The terminal displays an input form for the user to enter the proposal structure and detailed service content. The user enters the proposal structure and detailed information (e.g., service overview, target market, strategy, budget) into the form. The terminal sends the entered information to the server. In this step, the proposal structure and detailed service content are taken as input, and formatted data is generated as output to be sent to the server.

[0115] Step 3:

[0116] Collection and processing of related materials

[0117] The server searches for relevant materials through the storage service's API (e.g., Google Drive API, Dropbox API) based on the keywords and content structure entered by the user. The server receives a list of relevant files returned as search results. The server downloads the necessary files based on the list. In this step, the keywords and content structure are input, and the list of relevant files and downloaded materials are generated as output.

[0118] Step 4:

[0119] Data analysis and processing

[0120] The server provides the downloaded materials to a generative AI model (e.g., OpenAI GPT-4). The generative AI model analyzes the materials and extracts key points. This extracted information is then organized by the server in accordance with the proposal structure. In this step, the downloaded materials are used as input, and the extracted key points and organized data are generated as output.

[0121] Step 5:

[0122] Presentation generation process

[0123] The server launches the presentation creation software (e.g., Microsoft PowerPoint API, Google Slides API). The server issues a command to create a new presentation file. The server sends the key points extracted by the generative AI model to the presentation creation software. The presentation creation software automatically generates slides corresponding to each section. The generated slides are saved as a single presentation file. The server checks the location where the completed presentation file is saved. In this step, the input is organized data, and the output is a presentation file.

[0124] Step 6:

[0125] User notification and confirmation process

[0126] The server notifies the device of a link to the generated presentation file. The device displays the notified link to the user. The user clicks the link and checks the generated proposal. If necessary, the user can make corrections to the presentation using the device. The user checks the final proposal and submits it to the client or other relevant parties. In this step, the input is a link to the generated presentation file, and the output is the user checking and correcting the proposal.

[0127] The above is the flow of specific processing steps of the program of this system.

[0128] (Application example 1)

[0129] 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."

[0130] In conventional proposal creation systems, the process of users entering detailed information, collecting relevant materials, and then creating a proposal based on that information is time-consuming and labor-intensive. Furthermore, when proposing and explaining products in a virtual store, it is difficult to effectively suggest related products based on the user's interests and purchasing history. To solve these issues, a system is needed that can both streamline the proposal creation process and effectively propose products in a virtual store.

[0131] 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.

[0132] In this invention, the server includes means for a user to input the structure and detailed contents of a proposal, means for searching and retrieving related materials from a storage service, means for analyzing the retrieved materials using a generative AI model to extract key points, means for automatically generating a presentation file based on the extracted key points, means for notifying the user of a link to the generated presentation file, and means for making product suggestions in a virtual store based on the user's interests and purchase history. This allows users to efficiently create high-quality proposals, and also enables the virtual store to make product suggestions optimized for individual users.

[0133] "User" means a person or legal entity who uses this system to input the structure and details of a proposal and receives the generated presentation file.

[0134] A "proposal" is a document in which a user organizes information and summarizes the proposal for a specific purpose or project.

[0135] "Structure" refers to the layout and order of how each element and chapter of the proposal is arranged and organized.

[0136] "Detailed content" refers to the specific service content, product specifications, strategy, objectives, etc. included in the proposal.

[0137] "Storage service" is a general term for online services such as cloud storage and databases that allow you to store, share, and search for information.

[0138] A "generative AI model" is a system that uses artificial intelligence to automatically extract key points from input information and generate texts and presentations.

[0139] A "presentation file" is a slide-format file created to convey specific information in a visually easy-to-understand manner.

[0140] "Link" means the URL or path provided to a user to access the generated presentation file.

[0141] "Virtual store" refers to a virtual shopping environment that exists on the Internet, where users can browse and purchase products online.

[0142] An "interest" is when a user expresses interest in a particular category or product.

[0143] "Purchase history" is a record of products and services a user has purchased in the past.

[0144] The present invention is a system that automatically creates proposals by collecting related materials from a storage service when a user inputs the structure and details of the proposal. This system is composed of multiple means that work together to efficiently generate proposals. The system includes means for accepting user input, means for collecting information, means for analyzing materials, means for generating presentation files, and means for notifying the user of the generated files. In addition, in a virtual store, it also includes means for suggesting products based on the user's interests and purchasing history.

[0145] Program processing explanation

[0146] First, the user logs in to the system from the terminal. The terminal sends the user's login information (user name and password) to the server, and the server authenticates the user using the authentication method. If the authentication is successful, the user is redirected to their dashboard. Next, to create a new proposal, the user enters the proposal configuration and detailed service content. The terminal sends this information to the server.

[0147] The server searches for relevant materials through the storage service's API based on the keywords and content structure entered by the user. A list of relevant files is returned to the server from the storage service as a search result. The server receives the list and downloads the necessary files. The downloaded materials are provided to the generative AI model, which the server activates to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. The server organizes this extracted information based on the proposal structure.

[0148] Next, the server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which automatically generates slides corresponding to each section. The generated slides are saved as a single presentation file. The server then checks the location where the completed presentation file is saved and notifies the user of the access link.

[0149] As a concrete example, user "user123" inputs detailed information about a "new smartphone." The system collects past related reports and automatically generates a presentation as a proposal. The user is notified by email and can view the generated presentation file by clicking the download link. For example, the prompt text the user inputs might look like this:

[0150] "Collecting information to develop proposals for new smartphones, high-resolution cameras, and long-lasting batteries."

[0151] This system allows users to efficiently create high-quality proposals, and also makes it possible to propose products optimized for individual users in virtual stores.

[0152] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0153] Step 1:

[0154] A user logs into the system from a terminal. The terminal sends the user's login information (username and password) to the server. The server authenticates the user using an authentication method. If authentication is successful, the server redirects the user to the user dashboard. The inputs are the username and password, and the output returns whether the user authentication was successful or not.

[0155] Step 2:

[0156] To create a new proposal, a user inputs the proposal structure and detailed service content from their device. This information is sent from the device to the server. The server receives this input data and starts the proposal creation process. The inputs include the proposal structure and details, and the output is saved on the server.

[0157] Step 3:

[0158] The server searches for related materials based on the keywords and content structure entered by the user through the storage service's API. The server receives a list of related files from the storage service. The input is the keywords and content structure entered by the user, and the output is a list of related materials.

[0159] Step 4:

[0160] The server receives the list of relevant documents and downloads the necessary files. The downloaded documents are stored in the server. The input is the list of documents, and the output is the downloaded files.

[0161] Step 5:

[0162] The downloaded materials are provided to the generative AI model. The server runs the generative AI model to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. The downloaded materials are the input, and the extracted key points are the output.

[0163] Step 6:

[0164] The server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which then automatically generates slides corresponding to each section. The extracted key points are the input, and the presentation file is generated as the output.

[0165] Step 7:

[0166] The server checks the location of the generated presentation file and notifies the user of the access link. The user can access the provided link from their device and view the generated proposal. The input is the generated presentation file, and the output is the link notified to the user.

[0167] Step 8:

[0168] In the virtual store, product suggestions are made based on the user's interests and purchase history. The server collects related product information based on the user's input data and purchase history, and provides it as a proposal. The input is the user's interests and purchase history, and the output is the optimal product suggestion.

[0169] 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.

[0170] The present invention is a system that combines an emotion engine when a user inputs the structure and content of a proposal, thereby improving the proposal creation process efficiently and effectively.

[0171] A natural language explanation of the program's processing

[0172] 1. User Input Processing

[0173] First, the user logs in to the system from their terminal. The terminal sends the user's login information to the server, and the server authenticates the user using an authentication method. If authentication is successful, the server sends an instruction to the terminal to redirect to the user's dashboard. To create a new proposal, the user enters the proposal structure and detailed content. The terminal then sends this information to the server.

[0174] 2. Information Collection and Processing

[0175] The server calls the storage service's API to search for and retrieve relevant materials based on the information entered by the user. The storage service returns a list of relevant files to the server, and the server downloads the necessary files.

[0176] 3. Emotion Engine Processing

[0177] As the user enters information, the device's built-in emotion engine recognizes the user's emotions in real time. For example, if the user feels stressed, the emotion engine will send that information to the server, and the system will automatically adjust the interface and assistance functions based on the user's emotions.

[0178] 4. Data analysis and processing

[0179] The downloaded materials are provided to the generative AI model, which is then run by the server to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. The extracted information is then organized by the server into sections of the proposal.

[0180] 5. Presentation Generation Process

[0181] The server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which automatically generates slides corresponding to each section. The slides are saved as a single presentation file, and the server generates a link to the file and notifies the user.

[0182] 6. User Notification and Confirmation

[0183] The server sends a link to the generated presentation file to the device. The user accesses the link provided on the device and checks the generated proposal. The user can then revise the presentation content as necessary and check the final proposal.

[0184] Specific examples

[0185] As a specific example, consider a marketer at an advertising agency creating a proposal for a new social media marketing campaign. The user logs in to the system and begins creating a new proposal. The user enters details such as an overview of the service, target market, strategy, and budget. The emotion engine recognizes the user's emotions, and if the user is feeling stressed, for example, the server provides assistance to help the user relax. The server collects past success stories and marketing reports from a storage service, and a generative AI model summarizes the key points. The automatically generated presentation file is notified to the user, who can review it via a link and make any necessary revisions. Ultimately, a high-quality proposal is completed quickly and efficiently.

[0186] This system makes it possible to create high-quality proposals efficiently and quickly while taking into account the user's emotions.

[0187] The processing flow will be explained below.

[0188] Step 1:

[0189] A user logs in to the system from a terminal. The user enters a username and password on the login screen and presses the send button. The terminal sends this information to the server.

[0190] Step 2:

[0191] The server compares the received user information with the database and performs authentication. If authentication is successful, the server sends an instruction to the device to redirect to the user's dashboard.

[0192] Step 3:

[0193] The user clicks the "Create a new proposal" button on the dashboard, which opens a form on the device for entering the proposal structure and service details.

[0194] Step 4:

[0195] The user enters the proposal structure (e.g., objectives, target market, strategy, budget) and detailed service content. After the user has entered all the items, they press the send button. The terminal sends the input information to the server.

[0196] Step 5:

[0197] The server analyzes the received user input information and calls the storage service API to send a request to search for related materials.

[0198] Step 6:

[0199] The storage service returns a list of related files to the server, which then receives the list and downloads the necessary files.

[0200] Step 7:

[0201] As the user enters information, the device's built-in emotion engine recognizes the user's emotions in real time. For example, if the user is feeling stressed, the emotion engine will send that information to the server.

[0202] Step 8:

[0203] Based on the emotional information received by the server, the interface and assistance functions are automatically adjusted, and messages and guidelines are displayed to help the user relax.

[0204] Step 9:

[0205] The server provides the downloaded materials to the generative AI model, which then analyzes the materials and extracts key points and important information.

[0206] Step 10:

[0207] The generative AI model returns the extracted information to the server, which organizes it into sections of the proposal and determines the slide summaries for each section.

[0208] Step 11:

[0209] The server starts the presentation creation software, instructs it to create a new presentation file, and sends specific summaries for each slide to the presentation creation software.

[0210] Step 12:

[0211] The presentation software automatically generates slides and saves the completed slides as a single presentation file. The server confirms the location and link of the generated presentation file.

[0212] Step 13:

[0213] The server notifies the device of the link to the generated presentation file, and the device displays the notification to the user, who can click the link to view the generated proposal.

[0214] Step 14:

[0215] The user accesses the provided link on their device to view the generated proposal, revise the presentation content as needed, and review the final proposal.

[0216] This allows users to quickly and efficiently create high-quality proposals while taking their emotional state into account.

[0217] Example 2

[0218] 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."

[0219] Conventional proposal creation systems have the problem that users have to manually input the structure and details of the proposal, collect related materials, and summarize the main points, which takes a lot of time and effort.In addition, because the system does not take into account the user's emotions, the work often becomes stressful, which can ultimately affect the quality of the proposal.

[0220] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for the user to input the structure and detailed contents of the proposal, a means for recognizing the user's emotions in real time and adjusting the interface and assistance functions based on the emotion data, a means for searching and acquiring related materials from a storage service, a means for analyzing the acquired materials using a generative AI model and extracting key points, a means for automatically generating a presentation file based on the extracted key points, and a means for notifying the user of a link to the generated presentation file. This makes it possible to streamline the proposal creation process and quickly create high-quality proposals while taking user emotions into consideration.

[0221] A "proposal" is a document in which a user organizes and details information, plans, strategies, budgets, etc. regarding a specific idea, project, service or product.

[0222] "Storage service" means an online platform or system used to store, access, and manage data. Examples include cloud storage services.

[0223] A "generative AI model" is an algorithm or system that uses artificial intelligence techniques to analyze and generate data, typically for tasks such as natural language processing and image generation.

[0224] "Recognizing user emotions in real time" refers to technology that analyzes facial expressions, tone of voice, etc. in real time when an end user interacts with a system, and grasps the user's emotional state.

[0225] "Adjusting the interface and assistance functions" means dynamically changing the screen display of the system used by the user and the assistance functions provided in response to the user's emotional state.

[0226] A "presentation file" is an electronic document for visually structuring and presenting information, and is generally structured in slide format.

[0227] "Auto-generate" means that the system automatically performs a specified task (e.g., creating a presentation) based on input data and settings, with little or no manual user interaction.

[0228] "Providing a link" means communicating to the user the URL of the generated file or information in a format that the user can access.

[0229] The present invention is a system that automatically generates high-quality proposals by allowing users to input the structure and content of the proposal while taking into account changes in emotions during the process. This system provides users with a means to create proposals efficiently and effectively.

[0230] This system includes three main components: a server, a terminal, and a user. The specific processing will be explained below.

[0231] First, a user logs in to the system from a terminal. At this time, the terminal sends login information (user name and password) to the server, and the server performs secure user authentication using an authentication method (e.g., OAuth or JWT). If authentication is successful, the user is redirected to a dedicated dashboard.

[0232] To create a new proposal, the user inputs the structure and details of the proposal into the terminal. The terminal sends this input information to the server, which stores the received information in a database.

[0233] Next, the server calls the API of the storage service (e.g., Google Drive or Dropbox) to search for and retrieve materials related to the content entered by the user, and downloads the necessary files based on the file list returned by the storage service.

[0234] During the data entry process, the device's built-in emotion engine (such as Affectiva or IBM Watson Tone Analyzer) recognizes the user's emotions in real time. Emotional data is sent to the server, and if the user is feeling stressed, appropriate assistance functions (such as playing relaxing music or changing the interface) are provided.

[0235] The server inputs the downloaded materials into a generative AI model (e.g., OpenAI's GPT-4) and begins analyzing the materials. The generative AI model extracts key points and important information from the provided materials, and these key points are stored in a database.

[0236] The server then calls the API of the presentation creation software (e.g., Microsoft PowerPoint or Google Slides) to automatically generate a new presentation file based on the extracted key points. The generated presentation file is saved and a link to it is sent to the user.

[0237] The user accesses the link provided on their device, checks the content they entered and the presentation file generated by the system, and, if necessary, makes corrections using the online editing function before confirming and finalizing the proposal.

[0238] (Example)

[0239] Consider a case where a marketing professional at an advertising agency is creating a proposal for a new social media marketing campaign. The professional logs in to the system and clicks the "Create a New Proposal" button. They then enter details such as the target market, strategy, and budget. As they enter their information, an emotion engine recognizes the professional's emotions and notifies the server that they are under stress. While relaxing background music plays, the server collects past success stories from a storage service, and a generative AI model summarizes the key points. A presentation file is automatically generated, and a link is sent to the professional. The professional can review the presentation via the link and make any necessary revisions. This specific example demonstrates how proposal creation can be done quickly and efficiently.

[0240] (Example of a prompt)

[0241] 1. Enter the information required to create a proposal (e.g., service overview, target market, strategy, budget).

[0242] 2. Please explain in detail how the Emotion Engine recognizes the user's emotions and assists them when their stress level is high.

[0243] 3. Please explain in detail the process by which the generative AI model extracts key points from the provided materials.

[0244] 4. Please describe in natural language the process of generating a presentation file and notifying the user.

[0245] The above is an embodiment of the invention.

[0246] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0247] Step 1:

[0248] A user logs in to the system from a terminal. The user enters a username and password on the login page and clicks the login button. The terminal sends the entered authentication information (username and password) to the server. The server performs authentication using an authentication method (for example, OAuth or JWT) and compares it with the user information stored in the database. If authentication is successful, the server sends the URL of the user's dashboard page to the terminal, and the terminal redirects to this page.

[0249] Input: Username, Password

[0250] Data processing: The server searches the database and collates user information

[0251] Output: Dashboard URL upon successful authentication

[0252] Step 2:

[0253] The user clicks the "Create a new proposal" button on the dashboard to display an input screen for creating a new proposal. The user enters detailed information for each section of the proposal (e.g., service overview, target market, strategy, budget). The device sends this input information to the server, which then stores the received information in a database.

[0254] Input: Proposal structure and details

[0255] Data processing: Save to database

[0256] Output: Proposal input confirmation message

[0257] Step 3:

[0258] The server calls the API of the storage service (e.g., Google Drive, Dropbox) and searches for relevant materials based on the proposal details entered by the user. It then downloads the necessary files based on the file list returned by the storage service. The server then obtains the URL of the relevant materials.

[0259] Input: Proposal content entered by the user

[0260] Data processing: Calling the storage service API, obtaining the file list, and downloading

[0261] Output: URL of related material

[0262] Step 4:

[0263] While the user is entering the contents of a document or proposal, the device's built-in emotion engine (e.g., Affectiva, IBM Watson Tone Analyzer) analyzes the user's facial expressions and vocal tone in real time. The recognized emotion data is sent to the server, and if it determines that the user is feeling stressed, the server adjusts the interface and assistance functions. Specifically, it plays relaxing music or changes the color tone of the interface.

[0264] Input: User facial expressions and tone of voice

[0265] Data processing: Analysis by emotion engine and sending emotion data

[0266] Output: Optimized interface and assistance functions

[0267] Step 5:

[0268] The server provides the downloaded materials to a generative AI model (e.g., OpenAI's GPT-4) and begins analyzing the materials. The generative AI model extracts key points and important information from the provided materials. The extracted key points are stored in a database.

[0269] Input: Downloaded materials

[0270] Data processing: Analyzing data and extracting key points using generative AI models

[0271] Output: Extracted key information

[0272] Step 6:

[0273] The server launches presentation creation software (e.g., Google Slides API) and instructs it to create a new presentation file. Slides corresponding to each section are automatically generated based on key point information extracted from the generative AI model. The design and layout of the slides are automatically adjusted. The created presentation file is saved in storage, and a link to it is generated.

[0274] Input: Extracted gist information

[0275] Data processing: API call for presentation creation software and slide generation

[0276] Output: Presentation file link

[0277] Step 7:

[0278] The link to the generated presentation file is sent to the device. The user accesses the provided link on the device, checks the contents of the generated proposal, and, if necessary, uses the online editing function to make corrections and complete the final proposal.

[0279] Input: Presentation file link

[0280] Data processing: Link notification and file access

[0281] Output: Final proposal with online editing functionality

[0282] This completes the processing flow of this system. This series of processing steps enables users to create high-quality proposals efficiently and effectively.

[0283] (Application example 2)

[0284] 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."

[0285] Conventional proposal creation systems required users to manually collect and analyze a huge amount of data, which required a great deal of time and effort. Furthermore, the cumbersome process made users feel stressed, and the quality of the proposals created varied. Since factory and on-site workers are particularly required to create documents quickly and with high quality, improvements were needed to both improve efficiency and reduce stress.

[0286] 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.

[0287] In this invention, the server includes: means for a user to input the structure and detailed contents of a proposal; means for searching and retrieving related materials from a storage service; means for analyzing the retrieved materials using a generative AI model to extract key points; means for notifying the user of a link to the generated presentation file; and means including an emotion engine for recognizing the user's emotions in real time and automatically adjusting the system's interface and assistance functions based on those emotions. This enables the user to efficiently create high-quality proposals, and the emotion engine allows the user to work while reducing stress.

[0288] A "Proposal" is a document in which a User proposes a specific project or idea.

[0289] "Structure" refers to the way in which each section and content in a proposal is organized.

[0290] "Details" refer to the specific information and data that will be included in each section of the proposal.

[0291] "Storage Services" means cloud-based data storage services that allow documents and other data to be stored and accessed as needed.

[0292] "Document search" is the process of searching for and retrieving relevant documents and information needed to prepare a proposal.

[0293] A "generative AI model" is an artificial intelligence model used to analyze provided data and extract key points.

[0294] "Key points extraction" is the process of extracting important points and summaries from documents or information.

[0295] A "presentation file" is a digital file that visually represents the contents of the proposal in an easy-to-understand manner.

[0296] "Link notification" is the process of informing users of the access link for the generated presentation file.

[0297] The "emotion engine" is an engine that analyzes user emotions in real time and adjusts the system's behavior based on the results.

[0298] This invention is a system for making the proposal creation process efficient and effective, automatically generating proposals based on user-provided information using a cloud-based storage service and artificial intelligence (AI) models. It also includes an emotion engine that recognizes user emotions in real time and adjusts the system's interface and support functions based on those emotions.

[0299] Program processing overview

[0300] First, a user logs in from a device (e.g., smart glasses or a PC). At this time, the login information is sent to the server, and the server authenticates the user using an authentication method. If authentication is successful, the user is redirected to the dashboard and can start creating a new proposal.

[0301] When the user enters the structure and details of the proposal, the device sends this information to the server, which then searches for and retrieves relevant materials from a cloud-based storage service. At this point, the Emotion Engine analyzes the user's emotions in real time and provides a relaxation assistance function if it detects stress or fatigue.

[0302] The acquired materials are provided to a generative AI model on the server, which analyzes the materials and extracts key points. The extracted key points are then provided to presentation creation software, which automatically generates a presentation file. This presentation file is then stored in cloud storage, and the user is notified of its access link.

[0303] Specific examples

[0304] Suppose a worker in a factory uses smart glasses to create a maintenance manual for a new machine. The worker verbally inputs the work procedure and important points through the smart glasses. For example, the worker might input a prompt such as, "Create a maintenance manual for a new machine. Steps: 1. Turn off the power. 2. Remove the cover. 3. Replace part A. Important note: Be sure to check the safety devices." EmotionEngine detects that the worker is tired and suggests taking a short break. The generative AI model then analyzes this information and automatically generates a detailed maintenance manual.

[0305] As another example, when creating a work instruction proposing improvements to the efficiency of the manufacturing process to solve the problem of slow production speed, the user would enter, "Create a proposal for improving the efficiency of the manufacturing process. Current problem: slow production speed. Proposed solution: introduce automated equipment. See past success stories." If the worker shows high stress levels, the emotion engine will support the creation of the work instruction by suggesting relaxation techniques, and the AI ​​will analyze the materials and automatically generate the optimal proposal.

[0306] In this way, it is possible to reduce the burden on the user and create proposals quickly and with high quality.

[0307] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0308] Step 1:

[0309] User authentication

[0310] The user enters their login information on their device. The device sends the login information to the server, which then authenticates them. During this authentication process, the server checks the user information against its database to determine if authentication is successful. If authentication is successful, the session begins and the user is redirected to the dashboard.

[0311] Input: User login information

[0312] Output: Authentication result and dashboard screen

[0313] Step 2:

[0314] Enter the proposal details

[0315] The user inputs the structure and details of a new proposal on the device. The device sends this information to the server. The user then inputs the desired components using voice or text input.

[0316] Input: Proposal structure and details

[0317] Output: Proposal information sent to the server

[0318] Step 3:

[0319] Search for related materials

[0320] The server calls the storage service's API, searches for and retrieves related materials based on the proposal content entered by the user, specifically searching for related materials such as past proposals and references, and retrieves a list of them. The server then downloads the necessary files.

[0321] Input: Proposal Information

[0322] Output: Related documents list and downloaded documents

[0323] Step 4:

[0324] emotion recognition

[0325] While the user is entering their proposal, the device's built-in emotion engine recognizes their emotions in real time. The emotion engine analyzes their facial expressions and vocal tone to determine whether they are feeling stressed. If stress levels are high, the server provides assistance to encourage the user to relax.

[0326] Input: User's facial expression, voice tone

[0327] Output: User's emotional state, relaxation assist function

[0328] Step 5:

[0329] Data analysis and key points extraction

[0330] The server provides the downloaded materials to a generative AI model, which then analyzes the materials and extracts key points. The AI ​​model then analyzes the text content of the materials to detect and extract key points.

[0331] Input: Downloaded materials

[0332] Output: Extracted gist

[0333] Step 6:

[0334] Generate presentation files

[0335] The server launches the presentation creation software and automatically creates a presentation file based on the key points extracted by the generative AI model. The created file is saved in cloud storage and an access link is generated.

[0336] Input: Extracted gist

[0337] Output: Auto-generated presentation file, access link

[0338] Step 7:

[0339] User Notification

[0340] The server sends an access link for the generated presentation file to the terminal. The user accesses the provided link on the terminal and checks the generated proposal. If necessary, the user can revise the presentation content and make a final check.

[0341] Input: Access Link

[0342] Output: Proposal review and revision

[0343] In this way, the workload on the user is reduced and proposals can be created quickly and with high quality.

[0344] 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.

[0345] 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.

[0346] 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.

[0347] [Second embodiment]

[0348] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0349] 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.

[0350] 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).

[0351] 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.

[0352] 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.

[0353] 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).

[0354] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[0355] 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.

[0356] 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.

[0357] 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.

[0358] 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.

[0359] 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."

[0360] This invention is a system that automatically creates proposals by collecting related materials from storage services when a user inputs the structure and content of the proposal. This system is composed of multiple means, each of which works together to efficiently generate proposals.

[0361] A natural language explanation of the program's processing

[0362] 1. User Input Processing

[0363] First, the user logs in to the system from their terminal. The terminal sends the user's login information (user name and password) to the server, and the server authenticates the user using an authentication method. If authentication is successful, the user is redirected to their dashboard. Next, the user enters the proposal structure and detailed service content to create a new proposal. The terminal then sends this information to the server.

[0364] 2. Information Collection and Processing

[0365] The server uses the storage service's API to search for relevant materials based on the keywords and content structure entered by the user. The storage service returns a list of relevant files to the server as search results. The server receives the list and downloads the necessary files.

[0366] 3. Data analysis and processing

[0367] The downloaded materials are provided to the generative AI model, which is then run by the server to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. This extracted information is then organized by the server based on the proposal structure.

[0368] 4. Presentation Generation Process

[0369] Next, the server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which automatically generates slides corresponding to each section. The generated slides are saved as a single presentation file. The server then checks the location where the completed presentation file is saved and notifies the user of the access link.

[0370] 5. User Notification and Confirmation

[0371] Finally, the server sends a link to the generated presentation file to the device. The user accesses the provided link on the device and checks the generated proposal. If necessary, the user can make corrections to the presentation on the device and check the final proposal. In this way, a high-quality proposal is completed efficiently.

[0372] Specific examples

[0373] As a concrete example, consider a marketer working at an advertising agency creating a proposal for a new social media marketing campaign. The user logs in and starts creating a new proposal. The user enters details such as a service overview, target market, strategy, and budget. The server collects past success stories and marketing reports from a storage service, and a generative AI model summarizes the key points. The automatically generated presentation file is notified to the user, who can review it via a link, make any necessary revisions, and then submit it to the client.

[0374] This system allows for the efficient and rapid creation of high-quality proposals, significantly reducing the time and effort required for proposal work.

[0375] The processing flow will be explained below.

[0376] Step 1:

[0377] A user logs in to the system from a terminal. The user enters a username and password on the login screen and presses the send button. The terminal sends this information to the server.

[0378] Step 2:

[0379] The server compares the received user information with the database and performs authentication. If authentication is successful, the server sends an instruction to the device to redirect to the user's dashboard.

[0380] Step 3:

[0381] The user clicks the "Create a new proposal" button on the dashboard, which opens a form on the device for entering the proposal structure and service details.

[0382] Step 4:

[0383] The user enters the proposal structure (e.g., objectives, target market, strategy, budget) and detailed service content. After the user has entered all the items, he / she presses the send button. The terminal sends the input information to the server.

[0384] Step 5:

[0385] The server analyzes the received user input information and calls the storage service API to send a request to search for related materials.

[0386] Step 6:

[0387] The storage service returns a list of related files to the server, which then receives the list and downloads the necessary files.

[0388] Step 7:

[0389] The server provides the downloaded materials to the generative AI model, which then analyzes the materials and extracts key points and important information.

[0390] Step 8:

[0391] The generative AI model returns the extracted information to the server, which organizes it into sections of the proposal and determines the slide summaries for each section.

[0392] Step 9:

[0393] The server starts the presentation creation software, instructs it to create a new presentation file, and sends specific summaries for each slide to the presentation creation software.

[0394] Step 10:

[0395] The presentation software automatically generates slides and saves the completed slides as a single presentation file. The server confirms the location and link of the generated presentation file.

[0396] Step 11:

[0397] The server notifies the device of the link to the generated presentation file, and the device displays the notification to the user, who can click the link to view the generated proposal.

[0398] Step 12:

[0399] The user accesses the provided link on their device to view the generated proposal, revise the presentation content as needed, and review the final proposal.

[0400] This allows users to create high-quality proposals quickly and efficiently.

[0401] Example 1

[0402] 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."

[0403] The traditional proposal creation process was highly inefficient, requiring users to spend a significant amount of time gathering information, manually organizing documents, and then creating the final proposal. This also created a risk of missing important information, leading to inconsistent proposal quality. Furthermore, the process of standardizing documents in different formats was time-consuming and burdensome for users.

[0404] 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.

[0405] In this invention, the server includes means for a user to input the structure and detailed contents of a proposal, means for searching and retrieving related materials from a data storage device, means for analyzing the retrieved materials using an artificial intelligence model to extract key points, means for automatically generating a presentation material file based on the extracted key points, means for notifying the user of a link to the generated presentation material file, and means for the user to check the generated proposal via the link and make corrections as necessary. This enables users to efficiently and quickly create high-quality proposals, significantly reducing the time and effort required for proposal work.

[0406] "User" refers to a person who operates the system and creates and checks proposals.

[0407] A "data storage device" is a device or system for storing and managing data, such as a cloud service or server.

[0408] An "artificial intelligence model" is a set of algorithms, such as machine learning models or natural language processing models, used to analyze data and extract key points.

[0409] A "presentation materials file" is a presentation-style file that summarizes the contents of the proposal.

[0410] "Link" is the URL or shared path that users can access to view the generated presentation file.

[0411] "Authentication methods" are technologies and methods for verifying a user's identity and granting legitimate access rights.

[0412] The "user dashboard" is an operation screen that users can access after logging in to the system, and is an interface where they can create and manage proposals.

[0413] "Presentation material creation software" refers to software or tools for creating, editing, and saving presentation files.

[0414] "Notification means" refers to the means by which the system notifies the user of information and file access links.

[0415] This system allows users to input the structure and content of a proposal, and then collects related materials from a data storage device and automatically creates a presentation file.The system includes multiple means, each of which works together to efficiently generate a proposal.

[0416] First, a user accesses the system from a terminal and needs to enter their username and password on the login screen. The terminal sends this login information to the server. The server authenticates the user using an authentication method (e.g., OAuth 2.0) and, if authentication is successful, redirects the user to the dashboard. There, the user can enter the proposal structure and details to create a new proposal.

[0417] The information entered by the user is sent from the device to the server. The server uses a data storage device (e.g., a cloud storage service API, such as Google Drive API or Dropbox API) to search for and retrieve relevant materials. The server then downloads the retrieved materials.

[0418] The server then provides the acquired materials to an artificial intelligence model (e.g., the generative AI model "OpenAI GPT-4") to analyze the materials. The generative AI model analyzes the materials and extracts key points. This extracted information is then organized by the server based on the proposal structure.

[0419] Based on the organized information, the server launches presentation creation software (e.g., Microsoft PowerPoint API or Google Slides API) to create a new presentation file. The extracted key points are automatically generated as slides corresponding to each section and saved as a single presentation file. The server then generates a link to the saved presentation file and notifies the user of the link.

[0420] The user can access the link provided by the server from their device to check the generated proposal. If some edits are required, the user can modify the presentation file from their device and then check and submit the final proposal.

[0421] Here are some concrete examples of how this system can be used:

[0422] When a marketer working at an advertising agency wants to create a proposal for a new social media marketing campaign, the user logs in and clicks the "Create a New Proposal" button on their dashboard. They then enter detailed information such as a service overview, target market, strategy, and budget. The server uses the Google Drive API to collect past success stories and marketing reports, and a generative AI model (OpenAI GPT-4) extracts the key points. The user is then notified of a presentation file automatically generated using the Microsoft PowerPoint API. The user clicks the link to review the file, make any necessary revisions, and submit the final proposal to the client.

[0423] Examples of prompts include:

[0424] "Using the following materials, please write a proposal for a new social media marketing campaign. Include a description of your services, your target market, your strategy, and your budget."

[0425] By inputting this prompt sentence, the generative AI model can generate appropriate suggestions.

[0426] The above is an embodiment of this system.

[0427] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0428] Step 1:

[0429] User login process

[0430] A user accesses the system from a terminal and enters a username and password on the login screen. The terminal sends the entered login information to the server. The server verifies the received login information using an authentication method (e.g., OAuth 2.0). If authentication is successful, the server returns a redirect link to the user's dashboard to the terminal. In this step, the username and password are taken as input, and a dashboard link is generated as output.

[0431] Step 2:

[0432] Proposal content input processing

[0433] The user clicks the "Create a new proposal" button from the dashboard. The terminal displays an input form for the user to enter the proposal structure and detailed service content. The user enters the proposal structure and detailed information (e.g., service overview, target market, strategy, budget) into the form. The terminal sends the entered information to the server. In this step, the proposal structure and detailed service content are taken as input, and formatted data is generated as output to be sent to the server.

[0434] Step 3:

[0435] Collection and processing of related materials

[0436] The server searches for relevant materials through the storage service's API (e.g., Google Drive API, Dropbox API) based on the keywords and content structure entered by the user. The server receives a list of relevant files returned as search results. The server downloads the necessary files based on the list. In this step, the keywords and content structure are input, and the list of relevant files and downloaded materials are generated as output.

[0437] Step 4:

[0438] Data analysis and processing

[0439] The server provides the downloaded materials to a generative AI model (e.g., OpenAI GPT-4). The generative AI model analyzes the materials and extracts key points. This extracted information is then organized by the server in accordance with the proposal structure. In this step, the downloaded materials are used as input, and the extracted key points and organized data are generated as output.

[0440] Step 5:

[0441] Presentation generation process

[0442] The server launches the presentation creation software (e.g., Microsoft PowerPoint API, Google Slides API). The server issues a command to create a new presentation file. The server sends the key points extracted by the generative AI model to the presentation creation software. The presentation creation software automatically generates slides corresponding to each section. The generated slides are saved as a single presentation file. The server checks the location where the completed presentation file is saved. In this step, the input is organized data, and the output is a presentation file.

[0443] Step 6:

[0444] User notification and confirmation process

[0445] The server notifies the device of a link to the generated presentation file. The device displays the notified link to the user. The user clicks the link and checks the generated proposal. If necessary, the user can make corrections to the presentation using the device. The user checks the final proposal and submits it to the client or other relevant parties. In this step, the input is a link to the generated presentation file, and the output is the user checking and correcting the proposal.

[0446] The above is the flow of specific processing steps of the program of this system.

[0447] (Application example 1)

[0448] 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."

[0449] In conventional proposal creation systems, the process of users entering detailed information, collecting relevant materials, and then creating a proposal based on that information is time-consuming and labor-intensive. Furthermore, when proposing and explaining products in a virtual store, it is difficult to effectively suggest related products based on the user's interests and purchasing history. To solve these issues, a system is needed that can both streamline the proposal creation process and effectively propose products in a virtual store.

[0450] 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.

[0451] In this invention, the server includes means for a user to input the structure and detailed contents of a proposal, means for searching and retrieving related materials from a storage service, means for analyzing the retrieved materials using a generative AI model to extract key points, means for automatically generating a presentation file based on the extracted key points, means for notifying the user of a link to the generated presentation file, and means for making product suggestions in a virtual store based on the user's interests and purchase history. This allows users to efficiently create high-quality proposals, and also enables the virtual store to make product suggestions optimized for individual users.

[0452] "User" means a person or legal entity who uses this system to input the structure and details of a proposal and receives the generated presentation file.

[0453] A "proposal" is a document in which a user organizes information and summarizes the proposal for a specific purpose or project.

[0454] "Structure" refers to the layout and order of how each element and chapter of the proposal is arranged and organized.

[0455] "Detailed content" refers to the specific service content, product specifications, strategy, objectives, etc. included in the proposal.

[0456] "Storage service" is a general term for online services such as cloud storage and databases that allow you to store, share, and search for information.

[0457] A "generative AI model" is a system that uses artificial intelligence to automatically extract key points from input information and generate texts and presentations.

[0458] A "presentation file" is a slide-format file created to convey specific information in a visually easy-to-understand manner.

[0459] "Link" means the URL or path provided to a user to access the generated presentation file.

[0460] "Virtual store" refers to a virtual shopping environment that exists on the Internet, where users can browse and purchase products online.

[0461] An "interest" is when a user expresses interest in a particular category or product.

[0462] "Purchase history" is a record of products and services a user has purchased in the past.

[0463] The present invention is a system that automatically creates proposals by collecting related materials from a storage service when a user inputs the structure and details of the proposal. This system is composed of multiple means that work together to efficiently generate proposals. The system includes means for accepting user input, means for collecting information, means for analyzing materials, means for generating presentation files, and means for notifying the user of the generated files. In addition, in a virtual store, it also includes means for suggesting products based on the user's interests and purchasing history.

[0464] Program processing explanation

[0465] First, the user logs in to the system from the terminal. The terminal sends the user's login information (user name and password) to the server, and the server authenticates the user using the authentication method. If the authentication is successful, the user is redirected to their dashboard. Next, to create a new proposal, the user enters the proposal configuration and detailed service content. The terminal sends this information to the server.

[0466] The server searches for relevant materials through the storage service's API based on the keywords and content structure entered by the user. A list of relevant files is returned to the server from the storage service as a search result. The server receives the list and downloads the necessary files. The downloaded materials are provided to the generative AI model, which the server activates to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. The server organizes this extracted information based on the proposal structure.

[0467] Next, the server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which automatically generates slides corresponding to each section. The generated slides are saved as a single presentation file. The server then checks the location where the completed presentation file is saved and notifies the user of the access link.

[0468] As a concrete example, user "user123" inputs detailed information about a "new smartphone." The system collects past related reports and automatically generates a presentation as a proposal. The user is notified by email and can view the generated presentation file by clicking the download link. For example, the prompt text the user inputs might look like this:

[0469] "Collecting information to develop proposals for new smartphones, high-resolution cameras, and long-lasting batteries."

[0470] This system allows users to efficiently create high-quality proposals, and also makes it possible to propose products optimized for individual users in virtual stores.

[0471] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0472] Step 1:

[0473] A user logs into the system from a terminal. The terminal sends the user's login information (username and password) to the server. The server authenticates the user using an authentication method. If authentication is successful, the server redirects the user to the user dashboard. The inputs are the username and password, and the output returns whether the user authentication was successful or not.

[0474] Step 2:

[0475] To create a new proposal, a user inputs the proposal structure and detailed service content from their device. This information is sent from the device to the server. The server receives this input data and starts the proposal creation process. The inputs include the proposal structure and details, and the output is saved on the server.

[0476] Step 3:

[0477] The server searches for related materials based on the keywords and content structure entered by the user through the storage service's API. The server receives a list of related files from the storage service. The input is the keywords and content structure entered by the user, and the output is a list of related materials.

[0478] Step 4:

[0479] The server receives the list of relevant documents and downloads the necessary files. The downloaded documents are stored in the server. The input is the list of documents, and the output is the downloaded files.

[0480] Step 5:

[0481] The downloaded materials are provided to the generative AI model. The server runs the generative AI model to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. The downloaded materials are the input, and the extracted key points are the output.

[0482] Step 6:

[0483] The server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which then automatically generates slides corresponding to each section. The extracted key points are the input, and the presentation file is generated as the output.

[0484] Step 7:

[0485] The server checks the location of the generated presentation file and notifies the user of the access link. The user can access the provided link from their device and view the generated proposal. The input is the generated presentation file, and the output is the link notified to the user.

[0486] Step 8:

[0487] In the virtual store, product suggestions are made based on the user's interests and purchase history. The server collects related product information based on the user's input data and purchase history, and provides it as a proposal. The input is the user's interests and purchase history, and the output is the optimal product suggestion.

[0488] 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.

[0489] The present invention is a system that combines an emotion engine when a user inputs the structure and content of a proposal, thereby improving the proposal creation process efficiently and effectively.

[0490] A natural language explanation of the program's processing

[0491] 1. User Input Processing

[0492] First, the user logs in to the system from their terminal. The terminal sends the user's login information to the server, and the server authenticates the user using an authentication method. If authentication is successful, the server sends an instruction to the terminal to redirect to the user's dashboard. To create a new proposal, the user enters the proposal structure and detailed content. The terminal then sends this information to the server.

[0493] 2. Information Collection and Processing

[0494] The server calls the storage service's API to search for and retrieve relevant materials based on the information entered by the user. The storage service returns a list of relevant files to the server, and the server downloads the necessary files.

[0495] 3. Emotion Engine Processing

[0496] As the user enters information, the device's built-in emotion engine recognizes the user's emotions in real time. For example, if the user feels stressed, the emotion engine will send that information to the server, and the system will automatically adjust the interface and assistance functions based on the user's emotions.

[0497] 4. Data analysis and processing

[0498] The downloaded materials are provided to the generative AI model, which is then run by the server to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. The extracted information is then organized by the server into sections of the proposal.

[0499] 5. Presentation Generation Process

[0500] The server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which automatically generates slides corresponding to each section. The slides are saved as a single presentation file, and the server generates a link to the file and notifies the user.

[0501] 6. User Notification and Confirmation

[0502] The server sends a link to the generated presentation file to the device. The user accesses the link provided on the device and checks the generated proposal. The user can then revise the presentation content as necessary and check the final proposal.

[0503] Specific examples

[0504] As a specific example, consider a marketer at an advertising agency creating a proposal for a new social media marketing campaign. The user logs in to the system and begins creating a new proposal. The user enters details such as an overview of the service, target market, strategy, and budget. The emotion engine recognizes the user's emotions, and if the user is feeling stressed, for example, the server provides assistance to help the user relax. The server collects past success stories and marketing reports from a storage service, and a generative AI model summarizes the key points. The automatically generated presentation file is notified to the user, who can review it via a link and make any necessary revisions. Ultimately, a high-quality proposal is completed quickly and efficiently.

[0505] This system makes it possible to create high-quality proposals efficiently and quickly while taking into account the user's emotions.

[0506] The processing flow will be explained below.

[0507] Step 1:

[0508] A user logs in to the system from a terminal. The user enters a username and password on the login screen and presses the send button. The terminal sends this information to the server.

[0509] Step 2:

[0510] The server compares the received user information with the database and performs authentication. If authentication is successful, the server sends an instruction to the device to redirect to the user's dashboard.

[0511] Step 3:

[0512] The user clicks the "Create a new proposal" button on the dashboard, which opens a form on the device for entering the proposal structure and service details.

[0513] Step 4:

[0514] The user enters the proposal structure (e.g., objectives, target market, strategy, budget) and detailed service content. After the user has entered all the items, he / she presses the send button. The terminal sends the input information to the server.

[0515] Step 5:

[0516] The server analyzes the received user input information and calls the storage service API to send a request to search for related materials.

[0517] Step 6:

[0518] The storage service returns a list of related files to the server, which then receives the list and downloads the necessary files.

[0519] Step 7:

[0520] As the user enters information, the device's built-in emotion engine recognizes the user's emotions in real time. For example, if the user is feeling stressed, the emotion engine will send that information to the server.

[0521] Step 8:

[0522] Based on the emotional information received by the server, the interface and assistance functions are automatically adjusted, and messages and guidelines are displayed to help the user relax.

[0523] Step 9:

[0524] The server provides the downloaded materials to the generative AI model, which then analyzes the materials and extracts key points and important information.

[0525] Step 10:

[0526] The generative AI model returns the extracted information to the server, which organizes it into sections of the proposal and determines the slide summaries for each section.

[0527] Step 11:

[0528] The server starts the presentation creation software, instructs it to create a new presentation file, and sends specific summaries for each slide to the presentation creation software.

[0529] Step 12:

[0530] The presentation software automatically generates slides and saves the completed slides as a single presentation file. The server confirms the location and link of the generated presentation file.

[0531] Step 13:

[0532] The server notifies the device of the link to the generated presentation file, and the device displays the notification to the user, who can click the link to view the generated proposal.

[0533] Step 14:

[0534] The user accesses the provided link on their device to view the generated proposal, revise the presentation content as needed, and review the final proposal.

[0535] This allows users to quickly and efficiently create high-quality proposals while taking their emotional state into account.

[0536] Example 2

[0537] 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."

[0538] Conventional proposal creation systems have the problem that users have to manually input the structure and details of the proposal, collect related materials, and summarize the main points, which takes a lot of time and effort.In addition, because the system does not take into account the user's emotions, the work often becomes stressful, which can ultimately affect the quality of the proposal.

[0539] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for the user to input the structure and detailed contents of the proposal, a means for recognizing the user's emotions in real time and adjusting the interface and assistance functions based on the emotion data, a means for searching and acquiring related materials from a storage service, a means for analyzing the acquired materials using a generative AI model and extracting key points, a means for automatically generating a presentation file based on the extracted key points, and a means for notifying the user of a link to the generated presentation file. This makes it possible to streamline the proposal creation process and quickly create high-quality proposals while taking user emotions into consideration.

[0540] A "proposal" is a document in which a user organizes and details information, plans, strategies, budgets, etc. regarding a specific idea, project, service or product.

[0541] "Storage service" means an online platform or system used to store, access, and manage data. Examples include cloud storage services.

[0542] A "generative AI model" is an algorithm or system that uses artificial intelligence techniques to analyze and generate data, typically for tasks such as natural language processing and image generation.

[0543] "Recognizing user emotions in real time" refers to technology that analyzes facial expressions, tone of voice, etc. in real time when an end user interacts with a system, and grasps the user's emotional state.

[0544] "Adjusting the interface and assistance functions" means dynamically changing the screen display of the system used by the user and the assistance functions provided according to the user's emotional state.

[0545] A "presentation file" is an electronic document for visually structuring and presenting information, and is generally structured in slide format.

[0546] "Auto-generate" means that the system automatically performs a specified task (e.g., creating a presentation) based on input data and settings, with little or no manual user interaction.

[0547] "Providing a link" means communicating to the user the URL of the generated file or information in a format that the user can access.

[0548] The present invention is a system that automatically generates high-quality proposals by allowing users to input the structure and content of the proposal while taking into account changes in emotions during the process. This system provides users with a means to create proposals efficiently and effectively.

[0549] This system includes three main components: a server, a terminal, and a user. The specific processing will be explained below.

[0550] First, a user logs in to the system from a terminal. At this time, the terminal sends login information (user name and password) to the server, and the server performs secure user authentication using an authentication method (e.g., OAuth or JWT). If authentication is successful, the user is redirected to a dedicated dashboard.

[0551] To create a new proposal, the user inputs the structure and details of the proposal into the terminal. The terminal sends this input information to the server, which stores the received information in a database.

[0552] Next, the server calls the API of the storage service (e.g., Google Drive or Dropbox) to search for and retrieve materials related to the content entered by the user, and downloads the necessary files based on the file list returned by the storage service.

[0553] During the data entry process, the device's built-in emotion engine (such as Affectiva or IBM Watson Tone Analyzer) recognizes the user's emotions in real time. Emotional data is sent to the server, and if the user is feeling stressed, appropriate assistance functions (such as playing relaxing music or changing the interface) are provided.

[0554] The server inputs the downloaded materials into a generative AI model (e.g., OpenAI's GPT-4) and begins analyzing the materials. The generative AI model extracts key points and important information from the provided materials, and these key points are stored in a database.

[0555] The server then calls the API of the presentation creation software (e.g., Microsoft PowerPoint or Google Slides) to automatically generate a new presentation file based on the extracted key points. The generated presentation file is saved and a link to it is sent to the user.

[0556] The user accesses the link provided on their device, checks the content they entered and the presentation file generated by the system, and, if necessary, makes corrections using the online editing function before confirming and finalizing the proposal.

[0557] (Example)

[0558] Consider a case where a marketing professional at an advertising agency is creating a proposal for a new social media marketing campaign. The professional logs in to the system and clicks the "Create a New Proposal" button. They then enter details such as the target market, strategy, and budget. As they enter their information, an emotion engine recognizes the professional's emotions and notifies the server that they are under stress. While relaxing background music plays, the server collects past success stories from a storage service, and a generative AI model summarizes the key points. A presentation file is automatically generated, and a link is sent to the professional. The professional can review the presentation via the link and make any necessary revisions. This specific example demonstrates how proposal creation can be done quickly and efficiently.

[0559] (Example of a prompt)

[0560] 1. Enter the information required to create a proposal (e.g., service overview, target market, strategy, budget).

[0561] 2. Please explain in detail how the Emotion Engine recognizes the user's emotions and assists them when their stress level is high.

[0562] 3. Please explain in detail the process by which the generative AI model extracts key points from the provided materials.

[0563] 4. Please describe in natural language the process of generating a presentation file and notifying the user.

[0564] The above is an embodiment of the invention.

[0565] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0566] Step 1:

[0567] A user logs in to the system from a terminal. The user enters a username and password on the login page and clicks the login button. The terminal sends the entered authentication information (username and password) to the server. The server performs authentication using an authentication method (for example, OAuth or JWT) and compares it with the user information stored in the database. If authentication is successful, the server sends the URL of the user's dashboard page to the terminal, and the terminal redirects to this page.

[0568] Input: Username, Password

[0569] Data processing: The server searches the database and collates user information

[0570] Output: Dashboard URL upon successful authentication

[0571] Step 2:

[0572] The user clicks the "Create a new proposal" button on the dashboard to display an input screen for creating a new proposal. The user enters detailed information for each section of the proposal (e.g., service overview, target market, strategy, budget). The device sends this input information to the server, which then stores the received information in a database.

[0573] Input: Proposal structure and details

[0574] Data processing: Save to database

[0575] Output: Proposal input confirmation message

[0576] Step 3:

[0577] The server calls the API of the storage service (e.g., Google Drive, Dropbox) and searches for relevant materials based on the proposal details entered by the user. It then downloads the necessary files based on the file list returned by the storage service. The server then obtains the URL of the relevant materials.

[0578] Input: Proposal content entered by the user

[0579] Data processing: Calling the storage service API, obtaining the file list, and downloading

[0580] Output: URL of related material

[0581] Step 4:

[0582] While the user is entering the contents of a document or proposal, the device's built-in emotion engine (e.g., Affectiva, IBM Watson Tone Analyzer) analyzes the user's facial expressions and vocal tone in real time. The recognized emotion data is sent to the server, and if it determines that the user is feeling stressed, the server adjusts the interface and assistance functions. Specifically, it plays relaxing music or changes the color tone of the interface.

[0583] Input: User facial expressions and tone of voice

[0584] Data processing: Analysis by emotion engine and sending emotion data

[0585] Output: Optimized interface and assistance functions

[0586] Step 5:

[0587] The server provides the downloaded materials to a generative AI model (e.g., OpenAI's GPT-4) and begins analyzing the materials. The generative AI model extracts key points and important information from the provided materials. The extracted key points are stored in a database.

[0588] Input: Downloaded materials

[0589] Data processing: Analyzing data and extracting key points using generative AI models

[0590] Output: Extracted key information

[0591] Step 6:

[0592] The server launches presentation creation software (e.g., Google Slides API) and instructs it to create a new presentation file. Slides corresponding to each section are automatically generated based on key point information extracted from the generative AI model. The design and layout of the slides are automatically adjusted. The created presentation file is saved in storage, and a link to it is generated.

[0593] Input: Extracted gist information

[0594] Data processing: API call for presentation creation software and slide generation

[0595] Output: Presentation file link

[0596] Step 7:

[0597] The link to the generated presentation file is sent to the device. The user accesses the provided link on the device, checks the contents of the generated proposal, and, if necessary, uses the online editing function to make corrections and complete the final proposal.

[0598] Input: Presentation file link

[0599] Data processing: Link notification and file access

[0600] Output: Final proposal with online editing functionality

[0601] This completes the processing flow of this system. This series of processing steps enables users to create high-quality proposals efficiently and effectively.

[0602] (Application example 2)

[0603] 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."

[0604] Conventional proposal creation systems required users to manually collect and analyze a huge amount of data, which required a great deal of time and effort. Furthermore, the cumbersome process made users feel stressed, and the quality of the proposals created varied. Since factory and on-site workers are particularly required to create documents quickly and with high quality, improvements were needed to both improve efficiency and reduce stress.

[0605] 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.

[0606] In this invention, the server includes: means for a user to input the structure and detailed contents of a proposal; means for searching and retrieving related materials from a storage service; means for analyzing the retrieved materials using a generative AI model to extract key points; means for notifying the user of a link to the generated presentation file; and means including an emotion engine for recognizing the user's emotions in real time and automatically adjusting the system's interface and assistance functions based on those emotions. This enables the user to efficiently create high-quality proposals, and the emotion engine allows the user to work while reducing stress.

[0607] A "Proposal" is a document in which a User proposes a specific project or idea.

[0608] "Structure" refers to the way in which each section and content in a proposal is organized.

[0609] "Details" refer to the specific information and data that will be included in each section of the proposal.

[0610] "Storage Services" means cloud-based data storage services that allow documents and other data to be stored and accessed as needed.

[0611] "Document search" is the process of searching for and retrieving relevant documents and information needed to prepare a proposal.

[0612] A "generative AI model" is an artificial intelligence model used to analyze provided data and extract key points.

[0613] "Key points extraction" is the process of extracting important points and summaries from documents or information.

[0614] A "presentation file" is a digital file that visually represents the contents of the proposal in an easy-to-understand manner.

[0615] "Link notification" is the process of informing users of the access link for the generated presentation file.

[0616] The "emotion engine" is an engine that analyzes user emotions in real time and adjusts the system's behavior based on the results.

[0617] This invention is a system for making the proposal creation process efficient and effective, automatically generating proposals based on user-provided information using a cloud-based storage service and artificial intelligence (AI) models. It also includes an emotion engine that recognizes user emotions in real time and adjusts the system's interface and support functions based on those emotions.

[0618] Program processing overview

[0619] First, a user logs in from a device (e.g., smart glasses or a PC). At this time, the login information is sent to the server, and the server authenticates the user using an authentication method. If authentication is successful, the user is redirected to the dashboard and can start creating a new proposal.

[0620] When the user enters the structure and details of the proposal, the device sends this information to the server, which then searches for and retrieves relevant materials from a cloud-based storage service. At this point, the Emotion Engine analyzes the user's emotions in real time and provides a relaxation assistance function if it detects stress or fatigue.

[0621] The acquired materials are provided to a generative AI model on the server, which analyzes the materials and extracts key points. The extracted key points are then provided to presentation creation software, which automatically generates a presentation file. This presentation file is then stored in cloud storage, and the user is notified of its access link.

[0622] Specific examples

[0623] Suppose a worker in a factory uses smart glasses to create a maintenance manual for a new machine. The worker verbally inputs the work procedure and important points through the smart glasses. For example, the worker might input a prompt such as, "Create a maintenance manual for a new machine. Steps: 1. Turn off the power. 2. Remove the cover. 3. Replace part A. Important note: Be sure to check the safety devices." EmotionEngine detects that the worker is tired and suggests taking a short break. The generative AI model then analyzes this information and automatically generates a detailed maintenance manual.

[0624] As another example, when creating a work instruction proposing improvements to the efficiency of the manufacturing process to solve the problem of slow production speed, the user would enter, "Create a proposal for improving the efficiency of the manufacturing process. Current problem: slow production speed. Proposed solution: introduce automated equipment. See past success stories." If the worker shows high stress levels, the emotion engine will support the creation of the work instruction by suggesting relaxation techniques, and the AI ​​will analyze the materials and automatically generate the optimal proposal.

[0625] In this way, it is possible to reduce the burden on the user and create proposals quickly and with high quality.

[0626] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0627] Step 1:

[0628] User authentication

[0629] The user enters their login information on their device. The device sends the login information to the server, which then authenticates them. During this authentication process, the server checks the user information against its database to determine if authentication is successful. If authentication is successful, the session begins and the user is redirected to the dashboard.

[0630] Input: User login information

[0631] Output: Authentication result and dashboard screen

[0632] Step 2:

[0633] Enter the proposal details

[0634] The user inputs the structure and details of a new proposal on the device. The device sends this information to the server. The user then inputs the desired components using voice or text input.

[0635] Input: Proposal structure and details

[0636] Output: Proposal information sent to the server

[0637] Step 3:

[0638] Search for related materials

[0639] The server calls the storage service's API, searches for and retrieves related materials based on the proposal content entered by the user, specifically searching for related materials such as past proposals and references, and retrieves a list of them. The server then downloads the necessary files.

[0640] Input: Proposal Information

[0641] Output: Related documents list and downloaded documents

[0642] Step 4:

[0643] emotion recognition

[0644] While the user is entering their proposal, the device's built-in emotion engine recognizes their emotions in real time. The emotion engine analyzes their facial expressions and vocal tone to determine whether they are feeling stressed. If stress levels are high, the server provides assistance to encourage the user to relax.

[0645] Input: User's facial expression, voice tone

[0646] Output: User's emotional state, relaxation assist function

[0647] Step 5:

[0648] Data analysis and key points extraction

[0649] The server provides the downloaded materials to a generative AI model, which then analyzes the materials and extracts key points. The AI ​​model then analyzes the text content of the materials to detect and extract key points.

[0650] Input: Downloaded materials

[0651] Output: Extracted gist

[0652] Step 6:

[0653] Generate presentation files

[0654] The server launches the presentation creation software and automatically creates a presentation file based on the key points extracted by the generative AI model. The created file is saved in cloud storage and an access link is generated.

[0655] Input: Extracted gist

[0656] Output: Auto-generated presentation file, access link

[0657] Step 7:

[0658] User Notification

[0659] The server sends an access link for the generated presentation file to the terminal. The user accesses the provided link on the terminal and checks the generated proposal. If necessary, the user can revise the presentation content and make a final check.

[0660] Input: Access Link

[0661] Output: Proposal review and revision

[0662] In this way, the workload on the user is reduced and proposals can be created quickly and with high quality.

[0663] 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.

[0664] 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.

[0665] 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.

[0666] [Third embodiment]

[0667] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0668] 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.

[0669] 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).

[0670] 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.

[0671] 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.

[0672] 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).

[0673] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[0674] 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.

[0675] 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.

[0676] 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.

[0677] 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.

[0678] 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."

[0679] This invention is a system that automatically creates proposals by collecting related materials from storage services when a user inputs the structure and content of the proposal. This system is composed of multiple means, each of which works together to efficiently generate proposals.

[0680] A natural language explanation of the program's processing

[0681] 1. User Input Processing

[0682] First, the user logs in to the system from their terminal. The terminal sends the user's login information (user name and password) to the server, and the server authenticates the user using an authentication method. If authentication is successful, the user is redirected to their dashboard. Next, the user enters the proposal structure and detailed service content to create a new proposal. The terminal then sends this information to the server.

[0683] 2. Information Collection and Processing

[0684] The server uses the storage service's API to search for relevant materials based on the keywords and content structure entered by the user. The storage service returns a list of relevant files to the server as search results. The server receives the list and downloads the necessary files.

[0685] 3. Data analysis and processing

[0686] The downloaded materials are provided to the generative AI model, which is then run by the server to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. This extracted information is then organized by the server based on the proposal structure.

[0687] 4. Presentation Generation Process

[0688] Next, the server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which automatically generates slides corresponding to each section. The generated slides are saved as a single presentation file. The server then checks the location where the completed presentation file is saved and notifies the user of the access link.

[0689] 5. User Notification and Confirmation

[0690] Finally, the server sends a link to the generated presentation file to the device. The user accesses the provided link on the device and checks the generated proposal. If necessary, the user can make corrections to the presentation on the device and check the final proposal. In this way, a high-quality proposal is completed efficiently.

[0691] Specific examples

[0692] As a concrete example, consider a marketer working at an advertising agency creating a proposal for a new social media marketing campaign. The user logs in and starts creating a new proposal. The user enters details such as a service overview, target market, strategy, and budget. The server collects past success stories and marketing reports from a storage service, and a generative AI model summarizes the key points. The automatically generated presentation file is notified to the user, who can review it via a link, make any necessary revisions, and then submit it to the client.

[0693] This system allows for the efficient and rapid creation of high-quality proposals, significantly reducing the time and effort required for proposal work.

[0694] The processing flow will be explained below.

[0695] Step 1:

[0696] A user logs in to the system from a terminal. The user enters a username and password on the login screen and presses the send button. The terminal sends this information to the server.

[0697] Step 2:

[0698] The server compares the received user information with the database and performs authentication. If authentication is successful, the server sends an instruction to the device to redirect to the user's dashboard.

[0699] Step 3:

[0700] The user clicks the "Create a new proposal" button on the dashboard, which opens a form on the device for entering the proposal structure and service details.

[0701] Step 4:

[0702] The user enters the proposal structure (e.g., objectives, target market, strategy, budget) and detailed service content. After the user has entered all the items, they press the send button. The terminal sends the input information to the server.

[0703] Step 5:

[0704] The server analyzes the received user input information and calls the storage service API to send a request to search for related materials.

[0705] Step 6:

[0706] The storage service returns a list of related files to the server, which then receives the list and downloads the necessary files.

[0707] Step 7:

[0708] The server provides the downloaded materials to the generative AI model, which then analyzes the materials and extracts key points and important information.

[0709] Step 8:

[0710] The generative AI model returns the extracted information to the server, which organizes it into sections of the proposal and determines the slide summaries for each section.

[0711] Step 9:

[0712] The server starts the presentation creation software, instructs it to create a new presentation file, and sends specific summaries for each slide to the presentation creation software.

[0713] Step 10:

[0714] The presentation software automatically generates slides and saves the completed slides as a single presentation file. The server confirms the location and link of the generated presentation file.

[0715] Step 11:

[0716] The server notifies the device of the link to the generated presentation file, and the device displays the notification to the user, who can click the link to view the generated proposal.

[0717] Step 12:

[0718] The user accesses the provided link on their device to view the generated proposal, revise the presentation content as needed, and review the final proposal.

[0719] This allows users to create high-quality proposals quickly and efficiently.

[0720] Example 1

[0721] 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."

[0722] The traditional proposal creation process was highly inefficient, requiring users to spend a significant amount of time gathering information, manually organizing documents, and then creating the final proposal. This also created a risk of missing important information, leading to inconsistent proposal quality. Furthermore, the process of standardizing documents in different formats was time-consuming and burdensome for users.

[0723] 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.

[0724] In this invention, the server includes means for a user to input the structure and detailed contents of a proposal, means for searching and retrieving related materials from a data storage device, means for analyzing the retrieved materials using an artificial intelligence model to extract key points, means for automatically generating a presentation material file based on the extracted key points, means for notifying the user of a link to the generated presentation material file, and means for the user to check the generated proposal via the link and make corrections as necessary. This enables users to efficiently and quickly create high-quality proposals, significantly reducing the time and effort required for proposal work.

[0725] "User" refers to a person who operates the system and creates and checks proposals.

[0726] A "data storage device" is a device or system for storing and managing data, such as a cloud service or server.

[0727] An "artificial intelligence model" is a set of algorithms, such as machine learning models or natural language processing models, used to analyze data and extract key points.

[0728] A "presentation materials file" is a presentation-style file that summarizes the contents of the proposal.

[0729] "Link" is the URL or shared path that users can access to view the generated presentation file.

[0730] "Authentication methods" are technologies and methods for verifying a user's identity and granting legitimate access rights.

[0731] The "user dashboard" is an operation screen that users can access after logging in to the system, and is an interface where they can create and manage proposals.

[0732] "Presentation material creation software" refers to software or tools for creating, editing, and saving presentation files.

[0733] "Notification means" refers to the means by which the system notifies the user of information and file access links.

[0734] This system allows users to input the structure and content of a proposal, and then collects related materials from a data storage device and automatically creates a presentation file.The system includes multiple means, each of which works together to efficiently generate a proposal.

[0735] First, a user accesses the system from a terminal and needs to enter their username and password on the login screen. The terminal sends this login information to the server. The server authenticates the user using an authentication method (e.g., OAuth 2.0) and, if authentication is successful, redirects the user to the dashboard. There, the user can enter the proposal structure and details to create a new proposal.

[0736] The information entered by the user is sent from the device to the server. The server uses a data storage device (e.g., a cloud storage service API, such as Google Drive API or Dropbox API) to search for and retrieve relevant materials. The server then downloads the retrieved materials.

[0737] The server then provides the acquired materials to an artificial intelligence model (e.g., the generative AI model "OpenAI GPT-4") to analyze the materials. The generative AI model analyzes the materials and extracts key points. This extracted information is then organized by the server based on the proposal structure.

[0738] Based on the organized information, the server launches presentation creation software (e.g., Microsoft PowerPoint API or Google Slides API) to create a new presentation file. The extracted key points are automatically generated as slides corresponding to each section and saved as a single presentation file. The server then generates a link to the saved presentation file and notifies the user of the link.

[0739] The user can access the link provided by the server from their device to check the generated proposal. If some edits are required, the user can modify the presentation file from their device and then check and submit the final proposal.

[0740] Here are some concrete examples of how this system can be used:

[0741] When a marketer working at an advertising agency wants to create a proposal for a new social media marketing campaign, the user logs in and clicks the "Create a New Proposal" button on their dashboard. They then enter detailed information such as a service overview, target market, strategy, and budget. The server uses the Google Drive API to collect past success stories and marketing reports, and a generative AI model (OpenAI GPT-4) extracts the key points. The user is then notified of a presentation file automatically generated using the Microsoft PowerPoint API. The user clicks the link to review the file, make any necessary revisions, and submit the final proposal to the client.

[0742] Examples of prompts include:

[0743] "Using the following materials, please write a proposal for a new social media marketing campaign. Include a description of your services, your target market, your strategy, and your budget."

[0744] By inputting this prompt sentence, the generative AI model can generate appropriate suggestions.

[0745] The above is an embodiment of this system.

[0746] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0747] Step 1:

[0748] User login process

[0749] A user accesses the system from a terminal and enters a username and password on the login screen. The terminal sends the entered login information to the server. The server verifies the received login information using an authentication method (e.g., OAuth 2.0). If authentication is successful, the server returns a redirect link to the user's dashboard to the terminal. In this step, the username and password are taken as input, and a dashboard link is generated as output.

[0750] Step 2:

[0751] Proposal content input processing

[0752] The user clicks the "Create a new proposal" button from the dashboard. The terminal displays an input form for the user to enter the proposal structure and detailed service content. The user enters the proposal structure and detailed information (e.g., service overview, target market, strategy, budget) into the form. The terminal sends the entered information to the server. In this step, the proposal structure and detailed service content are taken as input, and formatted data is generated as output to be sent to the server.

[0753] Step 3:

[0754] Collection and processing of related materials

[0755] The server searches for relevant materials through the storage service's API (e.g., Google Drive API, Dropbox API) based on the keywords and content structure entered by the user. The server receives a list of relevant files returned as search results. The server downloads the necessary files based on the list. In this step, the keywords and content structure are input, and the list of relevant files and downloaded materials are generated as output.

[0756] Step 4:

[0757] Data analysis and processing

[0758] The server provides the downloaded materials to a generative AI model (e.g., OpenAI GPT-4). The generative AI model analyzes the materials and extracts key points. This extracted information is then organized by the server in accordance with the proposal structure. In this step, the downloaded materials are used as input, and the extracted key points and organized data are generated as output.

[0759] Step 5:

[0760] Presentation generation process

[0761] The server launches the presentation creation software (e.g., Microsoft PowerPoint API, Google Slides API). The server issues a command to create a new presentation file. The server sends the key points extracted by the generative AI model to the presentation creation software. The presentation creation software automatically generates slides corresponding to each section. The generated slides are saved as a single presentation file. The server checks the location where the completed presentation file is saved. In this step, the input is organized data, and the output is a presentation file.

[0762] Step 6:

[0763] User notification and confirmation process

[0764] The server notifies the device of a link to the generated presentation file. The device displays the notified link to the user. The user clicks the link and checks the generated proposal. If necessary, the user can make corrections to the presentation using the device. The user checks the final proposal and submits it to the client or other relevant parties. In this step, the input is a link to the generated presentation file, and the output is the user checking and correcting the proposal.

[0765] The above is the flow of specific processing steps of the program of this system.

[0766] (Application example 1)

[0767] 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."

[0768] In conventional proposal creation systems, the process of users entering detailed information, collecting relevant materials, and then creating a proposal based on that information is time-consuming and labor-intensive. Furthermore, when proposing and explaining products in a virtual store, it is difficult to effectively suggest related products based on the user's interests and purchasing history. To solve these issues, a system is needed that can both streamline the proposal creation process and effectively propose products in a virtual store.

[0769] 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.

[0770] In this invention, the server includes means for a user to input the structure and detailed contents of a proposal, means for searching and retrieving related materials from a storage service, means for analyzing the retrieved materials using a generative AI model to extract key points, means for automatically generating a presentation file based on the extracted key points, means for notifying the user of a link to the generated presentation file, and means for making product suggestions in a virtual store based on the user's interests and purchase history. This allows users to efficiently create high-quality proposals, and also enables the virtual store to make product suggestions optimized for individual users.

[0771] "User" means a person or legal entity who uses this system to input the structure and details of a proposal and receives the generated presentation file.

[0772] A "proposal" is a document in which a user organizes information and summarizes the proposal for a specific purpose or project.

[0773] "Structure" refers to the layout and order of how each element and chapter of the proposal is arranged and organized.

[0774] "Detailed content" refers to the specific service content, product specifications, strategy, objectives, etc. included in the proposal.

[0775] "Storage service" is a general term for online services such as cloud storage and databases that allow you to store, share, and search for information.

[0776] A "generative AI model" is a system that uses artificial intelligence to automatically extract key points from input information and generate texts and presentations.

[0777] A "presentation file" is a slide-format file created to convey specific information in a visually easy-to-understand manner.

[0778] "Link" means the URL or path provided to a user to access the generated presentation file.

[0779] "Virtual store" refers to a virtual shopping environment that exists on the Internet, where users can browse and purchase products online.

[0780] An "interest" is when a user expresses interest in a particular category or product.

[0781] "Purchase history" is a record of products and services a user has purchased in the past.

[0782] The present invention is a system that automatically creates proposals by collecting related materials from a storage service when a user inputs the structure and details of the proposal. This system is composed of multiple means that work together to efficiently generate proposals. The system includes means for accepting user input, means for collecting information, means for analyzing materials, means for generating presentation files, and means for notifying the user of the generated files. In addition, in a virtual store, it also includes means for suggesting products based on the user's interests and purchasing history.

[0783] Program processing explanation

[0784] First, the user logs in to the system from the terminal. The terminal sends the user's login information (user name and password) to the server, and the server authenticates the user using the authentication method. If the authentication is successful, the user is redirected to their dashboard. Next, to create a new proposal, the user enters the proposal configuration and detailed service content. The terminal sends this information to the server.

[0785] The server searches for relevant materials through the storage service's API based on the keywords and content structure entered by the user. A list of relevant files is returned to the server from the storage service as a search result. The server receives the list and downloads the necessary files. The downloaded materials are provided to the generative AI model, which the server activates to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. The server organizes this extracted information based on the proposal structure.

[0786] Next, the server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which automatically generates slides corresponding to each section. The generated slides are saved as a single presentation file. The server then checks the location where the completed presentation file is saved and notifies the user of the access link.

[0787] As a concrete example, user "user123" inputs detailed information about a "new smartphone." The system collects past related reports and automatically generates a presentation as a proposal. The user is notified by email and can view the generated presentation file by clicking the download link. For example, the prompt text the user inputs might look like this:

[0788] "Collecting information to develop proposals for new smartphones, high-resolution cameras, and long-lasting batteries."

[0789] This system allows users to efficiently create high-quality proposals, and also makes it possible to propose products optimized for individual users in virtual stores.

[0790] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0791] Step 1:

[0792] A user logs into the system from a terminal. The terminal sends the user's login information (username and password) to the server. The server authenticates the user using an authentication method. If authentication is successful, the server redirects the user to the user dashboard. The inputs are the username and password, and the output returns whether the user authentication was successful or not.

[0793] Step 2:

[0794] To create a new proposal, a user inputs the proposal structure and detailed service content from their device. This information is sent from the device to the server. The server receives this input data and starts the proposal creation process. The inputs include the proposal structure and details, and the output is saved on the server.

[0795] Step 3:

[0796] The server searches for related materials based on the keywords and content structure entered by the user through the storage service's API. The server receives a list of related files from the storage service. The input is the keywords and content structure entered by the user, and the output is a list of related materials.

[0797] Step 4:

[0798] The server receives the list of relevant documents and downloads the necessary files. The downloaded documents are stored in the server. The input is the list of documents, and the output is the downloaded files.

[0799] Step 5:

[0800] The downloaded materials are provided to the generative AI model. The server runs the generative AI model to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. The downloaded materials are the input, and the extracted key points are the output.

[0801] Step 6:

[0802] The server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which then automatically generates slides corresponding to each section. The extracted key points are the input, and the presentation file is generated as the output.

[0803] Step 7:

[0804] The server checks the location of the generated presentation file and notifies the user of the access link. The user can access the provided link from their device and view the generated proposal. The input is the generated presentation file, and the output is the link notified to the user.

[0805] Step 8:

[0806] In the virtual store, product suggestions are made based on the user's interests and purchase history. The server collects related product information based on the user's input data and purchase history, and provides it as a proposal. The input is the user's interests and purchase history, and the output is the optimal product suggestion.

[0807] 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.

[0808] The present invention is a system that combines an emotion engine when a user inputs the structure and content of a proposal, thereby improving the proposal creation process efficiently and effectively.

[0809] A natural language explanation of the program's processing

[0810] 1. User Input Processing

[0811] First, the user logs in to the system from their terminal. The terminal sends the user's login information to the server, and the server authenticates the user using an authentication method. If authentication is successful, the server sends an instruction to the terminal to redirect to the user's dashboard. To create a new proposal, the user enters the proposal structure and detailed content. The terminal then sends this information to the server.

[0812] 2. Information Collection and Processing

[0813] The server calls the storage service's API to search for and retrieve relevant materials based on the information entered by the user. The storage service returns a list of relevant files to the server, and the server downloads the necessary files.

[0814] 3. Emotion Engine Processing

[0815] As the user enters information, the device's built-in emotion engine recognizes the user's emotions in real time. For example, if the user feels stressed, the emotion engine will send that information to the server, and the system will automatically adjust the interface and assistance functions based on the user's emotions.

[0816] 4. Data analysis and processing

[0817] The downloaded materials are provided to the generative AI model, which is then run by the server to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. The extracted information is then organized by the server into sections of the proposal.

[0818] 5. Presentation Generation Process

[0819] The server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which automatically generates slides corresponding to each section. The slides are saved as a single presentation file, and the server generates a link to the file and notifies the user.

[0820] 6. User Notification and Confirmation

[0821] The server sends a link to the generated presentation file to the device. The user accesses the link provided on the device and checks the generated proposal. The user can then revise the presentation content as necessary and check the final proposal.

[0822] Specific examples

[0823] As a specific example, consider a marketer at an advertising agency creating a proposal for a new social media marketing campaign. The user logs in to the system and begins creating a new proposal. The user enters details such as an overview of the service, target market, strategy, and budget. The emotion engine recognizes the user's emotions, and if the user is feeling stressed, for example, the server provides assistance to help the user relax. The server collects past success stories and marketing reports from a storage service, and a generative AI model summarizes the key points. The automatically generated presentation file is notified to the user, who can review it via a link and make any necessary revisions. Ultimately, a high-quality proposal is completed quickly and efficiently.

[0824] This system makes it possible to create high-quality proposals efficiently and quickly while taking into account the user's emotions.

[0825] The processing flow will be explained below.

[0826] Step 1:

[0827] A user logs in to the system from a terminal. The user enters a username and password on the login screen and presses the send button. The terminal sends this information to the server.

[0828] Step 2:

[0829] The server compares the received user information with the database and performs authentication. If authentication is successful, the server sends an instruction to the device to redirect to the user's dashboard.

[0830] Step 3:

[0831] The user clicks the "Create a new proposal" button on the dashboard, which opens a form on the device for entering the proposal structure and service details.

[0832] Step 4:

[0833] The user enters the proposal structure (e.g., objectives, target market, strategy, budget) and detailed service content. After the user has entered all the items, they press the send button. The terminal sends the input information to the server.

[0834] Step 5:

[0835] The server analyzes the received user input information and calls the storage service API to send a request to search for related materials.

[0836] Step 6:

[0837] The storage service returns a list of related files to the server, which then receives the list and downloads the necessary files.

[0838] Step 7:

[0839] As the user enters information, the device's built-in emotion engine recognizes the user's emotions in real time. For example, if the user is feeling stressed, the emotion engine will send that information to the server.

[0840] Step 8:

[0841] Based on the emotional information received by the server, the interface and assistance functions are automatically adjusted, and messages and guidelines are displayed to help the user relax.

[0842] Step 9:

[0843] The server provides the downloaded materials to the generative AI model, which then analyzes the materials and extracts key points and important information.

[0844] Step 10:

[0845] The generative AI model returns the extracted information to the server, which organizes it into sections of the proposal and determines the slide summaries for each section.

[0846] Step 11:

[0847] The server starts the presentation creation software, instructs it to create a new presentation file, and sends specific summaries for each slide to the presentation creation software.

[0848] Step 12:

[0849] The presentation software automatically generates slides and saves the completed slides as a single presentation file. The server confirms the location and link of the generated presentation file.

[0850] Step 13:

[0851] The server notifies the device of the link to the generated presentation file, and the device displays the notification to the user, who can click the link to view the generated proposal.

[0852] Step 14:

[0853] The user accesses the provided link on their device to view the generated proposal, revise the presentation content as needed, and review the final proposal.

[0854] This allows users to quickly and efficiently create high-quality proposals while taking their emotional state into account.

[0855] Example 2

[0856] 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."

[0857] Conventional proposal creation systems have the problem that users have to manually input the structure and details of the proposal, collect related materials, and summarize the main points, which takes a lot of time and effort.In addition, because the system does not take into account the user's emotions, the work often becomes stressful, which can ultimately affect the quality of the proposal.

[0858] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for the user to input the structure and detailed contents of the proposal, a means for recognizing the user's emotions in real time and adjusting the interface and assistance functions based on the emotion data, a means for searching and acquiring related materials from a storage service, a means for analyzing the acquired materials using a generative AI model and extracting key points, a means for automatically generating a presentation file based on the extracted key points, and a means for notifying the user of a link to the generated presentation file. This makes it possible to streamline the proposal creation process and quickly create high-quality proposals while taking user emotions into consideration.

[0859] A "proposal" is a document in which a user organizes and details information, plans, strategies, budgets, etc. regarding a specific idea, project, service or product.

[0860] "Storage service" means an online platform or system used to store, access, and manage data. Examples include cloud storage services.

[0861] A "generative AI model" is an algorithm or system that uses artificial intelligence techniques to analyze and generate data, typically for tasks such as natural language processing and image generation.

[0862] "Recognizing user emotions in real time" refers to technology that analyzes facial expressions, tone of voice, etc. in real time when an end user interacts with a system, and grasps the user's emotional state.

[0863] "Adjusting the interface and assistance functions" means dynamically changing the screen display of the system used by the user and the assistance functions provided in response to the user's emotional state.

[0864] A "presentation file" is an electronic document for visually structuring and presenting information, and is generally structured in slide format.

[0865] "Auto-generate" means that the system automatically performs a specified task (e.g., creating a presentation) based on input data and settings, with little or no manual user interaction.

[0866] "Providing a link" means communicating to the user the URL of the generated file or information in a format that the user can access.

[0867] The present invention is a system that automatically generates high-quality proposals by allowing users to input the structure and content of the proposal while taking into account changes in emotions during the process. This system provides users with a means to create proposals efficiently and effectively.

[0868] This system includes three main components: a server, a terminal, and a user. The specific processing will be explained below.

[0869] First, a user logs in to the system from a terminal. At this time, the terminal sends login information (user name and password) to the server, and the server performs secure user authentication using an authentication method (e.g., OAuth or JWT). If authentication is successful, the user is redirected to a dedicated dashboard.

[0870] To create a new proposal, the user inputs the structure and details of the proposal into the terminal. The terminal sends this input information to the server, which stores the received information in a database.

[0871] Next, the server calls the API of the storage service (e.g., Google Drive or Dropbox) to search for and retrieve materials related to the content entered by the user, and downloads the necessary files based on the file list returned by the storage service.

[0872] During the data entry process, the device's built-in emotion engine (such as Affectiva or IBM Watson Tone Analyzer) recognizes the user's emotions in real time. Emotional data is sent to the server, and if the user is feeling stressed, appropriate assistance functions (such as playing relaxing music or changing the interface) are provided.

[0873] The server inputs the downloaded materials into a generative AI model (e.g., OpenAI's GPT-4) and begins analyzing the materials. The generative AI model extracts key points and important information from the provided materials, and these key points are stored in a database.

[0874] The server then calls the API of the presentation creation software (e.g., Microsoft PowerPoint or Google Slides) to automatically generate a new presentation file based on the extracted key points. The generated presentation file is saved and a link to it is sent to the user.

[0875] The user accesses the link provided on their device, checks the content they entered and the presentation file generated by the system, and, if necessary, makes corrections using the online editing function before confirming and finalizing the proposal.

[0876] (Example)

[0877] Consider a case where a marketing professional at an advertising agency is creating a proposal for a new social media marketing campaign. The professional logs in to the system and clicks the "Create a New Proposal" button. They then enter details such as the target market, strategy, and budget. As they enter their information, an emotion engine recognizes the professional's emotions and notifies the server that they are under stress. While relaxing background music plays, the server collects past success stories from a storage service, and a generative AI model summarizes the key points. A presentation file is automatically generated, and a link is sent to the professional. The professional can review the presentation via the link and make any necessary revisions. This specific example demonstrates how proposal creation can be done quickly and efficiently.

[0878] (Example of a prompt)

[0879] 1. Enter the information required to create a proposal (e.g., service overview, target market, strategy, budget).

[0880] 2. Please explain in detail how the Emotion Engine recognizes the user's emotions and assists them when their stress level is high.

[0881] 3. Please explain in detail the process by which the generative AI model extracts key points from the provided materials.

[0882] 4. Please describe in natural language the process of generating a presentation file and notifying the user.

[0883] The above is an embodiment of the invention.

[0884] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0885] Step 1:

[0886] A user logs in to the system from a terminal. The user enters a username and password on the login page and clicks the login button. The terminal sends the entered authentication information (username and password) to the server. The server performs authentication using an authentication method (for example, OAuth or JWT) and compares it with the user information stored in the database. If authentication is successful, the server sends the URL of the user's dashboard page to the terminal, and the terminal redirects to this page.

[0887] Input: Username, Password

[0888] Data processing: The server searches the database and collates user information

[0889] Output: Dashboard URL upon successful authentication

[0890] Step 2:

[0891] The user clicks the "Create a new proposal" button on the dashboard to display an input screen for creating a new proposal. The user enters detailed information for each section of the proposal (e.g., service overview, target market, strategy, budget). The device sends this input information to the server, which then stores the received information in a database.

[0892] Input: Proposal structure and details

[0893] Data processing: Save to database

[0894] Output: Proposal input confirmation message

[0895] Step 3:

[0896] The server calls the API of the storage service (e.g., Google Drive, Dropbox) and searches for relevant materials based on the proposal details entered by the user. It then downloads the necessary files based on the file list returned by the storage service. The server then obtains the URL of the relevant materials.

[0897] Input: Proposal content entered by the user

[0898] Data processing: Calling the storage service API, obtaining the file list, and downloading

[0899] Output: URL of related material

[0900] Step 4:

[0901] While the user is entering the contents of a document or proposal, the device's built-in emotion engine (e.g., Affectiva, IBM Watson Tone Analyzer) analyzes the user's facial expressions and vocal tone in real time. The recognized emotion data is sent to the server, and if it determines that the user is feeling stressed, the server adjusts the interface and assistance functions. Specifically, it plays relaxing music or changes the color tone of the interface.

[0902] Input: User facial expressions and tone of voice

[0903] Data processing: Analysis by emotion engine and sending emotion data

[0904] Output: Optimized interface and assistance functions

[0905] Step 5:

[0906] The server provides the downloaded materials to a generative AI model (e.g., OpenAI's GPT-4) and begins analyzing the materials. The generative AI model extracts key points and important information from the provided materials. The extracted key points are stored in a database.

[0907] Input: Downloaded materials

[0908] Data processing: Analyzing data and extracting key points using generative AI models

[0909] Output: Extracted key information

[0910] Step 6:

[0911] The server launches presentation creation software (e.g., Google Slides API) and instructs it to create a new presentation file. Slides corresponding to each section are automatically generated based on key point information extracted from the generative AI model. The design and layout of the slides are automatically adjusted. The created presentation file is saved in storage, and a link to it is generated.

[0912] Input: Extracted gist information

[0913] Data processing: API call for presentation creation software and slide generation

[0914] Output: Presentation file link

[0915] Step 7:

[0916] The link to the generated presentation file is sent to the device. The user accesses the provided link on the device, checks the contents of the generated proposal, and, if necessary, uses the online editing function to make corrections and complete the final proposal.

[0917] Input: Presentation file link

[0918] Data processing: Link notification and file access

[0919] Output: Final proposal with online editing functionality

[0920] This completes the processing flow of this system. This series of processing steps enables users to create high-quality proposals efficiently and effectively.

[0921] (Application example 2)

[0922] 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."

[0923] Conventional proposal creation systems required users to manually collect and analyze a huge amount of data, which required a great deal of time and effort. Furthermore, the cumbersome process made users feel stressed, and the quality of the proposals created varied. Since factory and on-site workers are particularly required to create documents quickly and with high quality, improvements were needed to both improve efficiency and reduce stress.

[0924] 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.

[0925] In this invention, the server includes: means for a user to input the structure and detailed contents of a proposal; means for searching and retrieving related materials from a storage service; means for analyzing the retrieved materials using a generative AI model to extract key points; means for notifying the user of a link to the generated presentation file; and means including an emotion engine for recognizing the user's emotions in real time and automatically adjusting the system's interface and assistance functions based on those emotions. This enables the user to efficiently create high-quality proposals, and the emotion engine allows the user to work while reducing stress.

[0926] A "Proposal" is a document in which a User proposes a specific project or idea.

[0927] "Structure" refers to the way in which each section and content in a proposal is organized.

[0928] "Details" refer to the specific information and data that will be included in each section of the proposal.

[0929] "Storage Services" means cloud-based data storage services that allow documents and other data to be stored and accessed as needed.

[0930] "Document search" is the process of searching for and retrieving relevant documents and information needed to prepare a proposal.

[0931] A "generative AI model" is an artificial intelligence model used to analyze provided data and extract key points.

[0932] "Key points extraction" is the process of extracting important points and summaries from documents or information.

[0933] A "presentation file" is a digital file that visually represents the contents of the proposal in an easy-to-understand manner.

[0934] "Link notification" is the process of informing users of the access link for the generated presentation file.

[0935] The "emotion engine" is an engine that analyzes user emotions in real time and adjusts the system's behavior based on the results.

[0936] This invention is a system for making the proposal creation process efficient and effective, automatically generating proposals based on user-provided information using a cloud-based storage service and artificial intelligence (AI) models. It also includes an emotion engine that recognizes user emotions in real time and adjusts the system's interface and support functions based on those emotions.

[0937] Program processing overview

[0938] First, a user logs in from a device (e.g., smart glasses or a PC). At this time, the login information is sent to the server, and the server authenticates the user using an authentication method. If authentication is successful, the user is redirected to the dashboard and can start creating a new proposal.

[0939] When the user enters the structure and details of the proposal, the device sends this information to the server, which then searches for and retrieves relevant materials from a cloud-based storage service. At this point, the Emotion Engine analyzes the user's emotions in real time and provides a relaxation assistance function if it detects stress or fatigue.

[0940] The acquired materials are provided to a generative AI model on the server, which analyzes the materials and extracts key points. The extracted key points are then provided to presentation creation software, which automatically generates a presentation file. This presentation file is then stored in cloud storage, and the user is notified of its access link.

[0941] Specific examples

[0942] Suppose a worker in a factory uses smart glasses to create a maintenance manual for a new machine. The worker verbally inputs the work procedure and important points through the smart glasses. For example, the worker might input a prompt such as, "Create a maintenance manual for a new machine. Steps: 1. Turn off the power. 2. Remove the cover. 3. Replace part A. Important note: Be sure to check the safety devices." EmotionEngine detects that the worker is tired and suggests taking a short break. The generative AI model then analyzes this information and automatically generates a detailed maintenance manual.

[0943] As another example, when creating a work instruction proposing improvements to the efficiency of the manufacturing process to solve the problem of slow production speed, the user would enter, "Create a proposal for improving the efficiency of the manufacturing process. Current problem: slow production speed. Proposed solution: introduce automated equipment. See past success stories." If the worker shows high stress levels, the emotion engine will support the creation of the work instruction by suggesting relaxation techniques, and the AI ​​will analyze the materials and automatically generate the optimal proposal.

[0944] In this way, it is possible to reduce the burden on the user and create proposals quickly and with high quality.

[0945] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0946] Step 1:

[0947] User authentication

[0948] The user enters their login information on their device. The device sends the login information to the server, which then authenticates them. During this authentication process, the server checks the user information against its database to determine if authentication is successful. If authentication is successful, the session begins and the user is redirected to the dashboard.

[0949] Input: User login information

[0950] Output: Authentication result and dashboard screen

[0951] Step 2:

[0952] Enter the proposal details

[0953] The user inputs the structure and details of a new proposal on the device. The device sends this information to the server. The user then inputs the desired components using voice or text input.

[0954] Input: Proposal structure and details

[0955] Output: Proposal information sent to the server

[0956] Step 3:

[0957] Search for related materials

[0958] The server calls the storage service's API, searches for and retrieves related materials based on the proposal content entered by the user, specifically searching for related materials such as past proposals and references, and retrieves a list of them. The server then downloads the necessary files.

[0959] Input: Proposal Information

[0960] Output: Related documents list and downloaded documents

[0961] Step 4:

[0962] emotion recognition

[0963] While the user is entering their proposal, the device's built-in emotion engine recognizes their emotions in real time. The emotion engine analyzes their facial expressions and vocal tone to determine whether they are feeling stressed. If stress levels are high, the server provides assistance to encourage the user to relax.

[0964] Input: User's facial expression, voice tone

[0965] Output: User's emotional state, relaxation assist function

[0966] Step 5:

[0967] Data analysis and key points extraction

[0968] The server provides the downloaded materials to a generative AI model, which then analyzes the materials and extracts key points. The AI ​​model then analyzes the text content of the materials to detect and extract key points.

[0969] Input: Downloaded materials

[0970] Output: Extracted gist

[0971] Step 6:

[0972] Generate presentation files

[0973] The server launches the presentation creation software and automatically creates a presentation file based on the key points extracted by the generative AI model. The created file is saved in cloud storage and an access link is generated.

[0974] Input: Extracted gist

[0975] Output: Auto-generated presentation file, access link

[0976] Step 7:

[0977] User Notification

[0978] The server sends an access link for the generated presentation file to the terminal. The user accesses the provided link on the terminal and checks the generated proposal. If necessary, the user can revise the presentation content and make a final check.

[0979] Input: Access Link

[0980] Output: Proposal review and revision

[0981] In this way, the workload on the user is reduced and proposals can be created quickly and with high quality.

[0982] 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.

[0983] 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.

[0984] 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.

[0985] [Fourth embodiment]

[0986] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0987] 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.

[0988] 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).

[0989] 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.

[0990] 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.

[0991] 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).

[0992] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for 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.

[0993] 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.

[0994] 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.

[0995] 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.

[0996] 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.

[0997] 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.

[0998] 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."

[0999] This invention is a system that automatically creates proposals by collecting related materials from storage services when a user inputs the structure and content of the proposal. This system is composed of multiple means, each of which works together to efficiently generate proposals.

[1000] A natural language explanation of the program's processing

[1001] 1. User Input Processing

[1002] First, the user logs in to the system from their terminal. The terminal sends the user's login information (user name and password) to the server, and the server authenticates the user using an authentication method. If authentication is successful, the user is redirected to their dashboard. Next, the user enters the proposal structure and detailed service content to create a new proposal. The terminal then sends this information to the server.

[1003] 2. Information Collection and Processing

[1004] The server uses the storage service's API to search for relevant materials based on the keywords and content structure entered by the user. The storage service returns a list of relevant files to the server as search results. The server receives the list and downloads the necessary files.

[1005] 3. Data analysis and processing

[1006] The downloaded materials are provided to the generative AI model, which is then run by the server to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. This extracted information is then organized by the server based on the proposal structure.

[1007] 4. Presentation Generation Process

[1008] Next, the server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which automatically generates slides corresponding to each section. The generated slides are saved as a single presentation file. The server then checks the location where the completed presentation file is saved and notifies the user of the access link.

[1009] 5. User Notification and Confirmation

[1010] Finally, the server sends a link to the generated presentation file to the device. The user accesses the provided link on the device and checks the generated proposal. If necessary, the user can make corrections to the presentation on the device and check the final proposal. In this way, a high-quality proposal is completed efficiently.

[1011] Specific examples

[1012] As a concrete example, consider a marketer working at an advertising agency creating a proposal for a new social media marketing campaign. The user logs in and starts creating a new proposal. The user enters details such as a service overview, target market, strategy, and budget. The server collects past success stories and marketing reports from a storage service, and a generative AI model summarizes the key points. The automatically generated presentation file is notified to the user, who can review it via a link, make any necessary revisions, and then submit it to the client.

[1013] This system allows for the efficient and rapid creation of high-quality proposals, significantly reducing the time and effort required for proposal work.

[1014] The processing flow will be explained below.

[1015] Step 1:

[1016] A user logs in to the system from a terminal. The user enters a username and password on the login screen and presses the send button. The terminal sends this information to the server.

[1017] Step 2:

[1018] The server compares the received user information with the database and performs authentication. If authentication is successful, the server sends an instruction to the device to redirect to the user's dashboard.

[1019] Step 3:

[1020] The user clicks the "Create a new proposal" button on the dashboard, which opens a form on the device for entering the proposal structure and service details.

[1021] Step 4:

[1022] The user enters the proposal structure (e.g., objectives, target market, strategy, budget) and detailed service content. After the user has entered all the items, they press the send button. The terminal sends the input information to the server.

[1023] Step 5:

[1024] The server analyzes the received user input information and calls the storage service API to send a request to search for related materials.

[1025] Step 6:

[1026] The storage service returns a list of related files to the server, which then receives the list and downloads the necessary files.

[1027] Step 7:

[1028] The server provides the downloaded materials to the generative AI model, which then analyzes the materials and extracts key points and important information.

[1029] Step 8:

[1030] The generative AI model returns the extracted information to the server, which organizes it into sections of the proposal and determines the slide summaries for each section.

[1031] Step 9:

[1032] The server starts the presentation creation software, instructs it to create a new presentation file, and sends specific summaries for each slide to the presentation creation software.

[1033] Step 10:

[1034] The presentation software automatically generates slides and saves the completed slides as a single presentation file. The server confirms the location and link of the generated presentation file.

[1035] Step 11:

[1036] The server notifies the device of the link to the generated presentation file, and the device displays the notification to the user, who can click the link to view the generated proposal.

[1037] Step 12:

[1038] The user accesses the provided link on their device to view the generated proposal, revise the presentation content as needed, and review the final proposal.

[1039] This allows users to create high-quality proposals quickly and efficiently.

[1040] Example 1

[1041] 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."

[1042] The traditional proposal creation process was highly inefficient, requiring users to spend a significant amount of time gathering information, manually organizing documents, and then creating the final proposal. This also created a risk of missing important information, leading to inconsistent proposal quality. Furthermore, the process of standardizing documents in different formats was time-consuming and burdensome for users.

[1043] 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.

[1044] In this invention, the server includes means for a user to input the structure and detailed contents of a proposal, means for searching and retrieving related materials from a data storage device, means for analyzing the retrieved materials using an artificial intelligence model to extract key points, means for automatically generating a presentation material file based on the extracted key points, means for notifying the user of a link to the generated presentation material file, and means for the user to check the generated proposal via the link and make corrections as necessary. This enables users to efficiently and quickly create high-quality proposals, significantly reducing the time and effort required for proposal work.

[1045] "User" refers to a person who operates the system and creates and checks proposals.

[1046] A "data storage device" is a device or system for storing and managing data, such as a cloud service or server.

[1047] An "artificial intelligence model" is a set of algorithms, such as machine learning models or natural language processing models, used to analyze data and extract key points.

[1048] A "presentation materials file" is a presentation-style file that summarizes the contents of the proposal.

[1049] "Link" is the URL or shared path that users can access to view the generated presentation file.

[1050] "Authentication methods" are technologies and methods for verifying a user's identity and granting legitimate access rights.

[1051] The "user dashboard" is an operation screen that users can access after logging in to the system, and is an interface where they can create and manage proposals.

[1052] "Presentation material creation software" refers to software or tools for creating, editing, and saving presentation files.

[1053] "Notification means" refers to the means by which the system notifies the user of information and file access links.

[1054] This system allows users to input the structure and content of a proposal, and then collects related materials from a data storage device and automatically creates a presentation file.The system includes multiple means, each of which works together to efficiently generate a proposal.

[1055] First, a user accesses the system from a terminal and needs to enter their username and password on the login screen. The terminal sends this login information to the server. The server authenticates the user using an authentication method (e.g., OAuth 2.0) and, if authentication is successful, redirects the user to the dashboard. There, the user can enter the proposal structure and details to create a new proposal.

[1056] The information entered by the user is sent from the device to the server. The server uses a data storage device (e.g., a cloud storage service API, such as Google Drive API or Dropbox API) to search for and retrieve relevant materials. The server then downloads the retrieved materials.

[1057] The server then provides the acquired materials to an artificial intelligence model (e.g., the generative AI model "OpenAI GPT-4") to analyze the materials. The generative AI model analyzes the materials and extracts key points. This extracted information is then organized by the server based on the proposal structure.

[1058] Based on the organized information, the server launches presentation creation software (e.g., Microsoft PowerPoint API or Google Slides API) to create a new presentation file. The extracted key points are automatically generated as slides corresponding to each section and saved as a single presentation file. The server then generates a link to the saved presentation file and notifies the user of the link.

[1059] The user can access the link provided by the server from their device to check the generated proposal. If some edits are required, the user can modify the presentation file from their device and then check and submit the final proposal.

[1060] Here are some concrete examples of how this system can be used:

[1061] When a marketer working at an advertising agency wants to create a proposal for a new social media marketing campaign, the user logs in and clicks the "Create a New Proposal" button on their dashboard. They then enter detailed information such as a service overview, target market, strategy, and budget. The server uses the Google Drive API to collect past success stories and marketing reports, and a generative AI model (OpenAI GPT-4) extracts the key points. The user is then notified of a presentation file automatically generated using the Microsoft PowerPoint API. The user clicks the link to review the file, make any necessary revisions, and submit the final proposal to the client.

[1062] Examples of prompts include:

[1063] "Using the following materials, please write a proposal for a new social media marketing campaign. Include a description of your services, your target market, your strategy, and your budget."

[1064] By inputting this prompt sentence, the generative AI model can generate appropriate suggestions.

[1065] The above is an embodiment of this system.

[1066] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1067] Step 1:

[1068] User login process

[1069] A user accesses the system from a terminal and enters a username and password on the login screen. The terminal sends the entered login information to the server. The server verifies the received login information using an authentication method (e.g., OAuth 2.0). If authentication is successful, the server returns a redirect link to the user's dashboard to the terminal. In this step, the username and password are taken as input, and a dashboard link is generated as output.

[1070] Step 2:

[1071] Proposal content input processing

[1072] The user clicks the "Create a new proposal" button from the dashboard. The terminal displays an input form for the user to enter the proposal structure and detailed service content. The user enters the proposal structure and detailed information (e.g., service overview, target market, strategy, budget) into the form. The terminal sends the entered information to the server. In this step, the proposal structure and detailed service content are taken as input, and formatted data is generated as output to be sent to the server.

[1073] Step 3:

[1074] Collection and processing of related materials

[1075] The server searches for relevant materials through the storage service's API (e.g., Google Drive API, Dropbox API) based on the keywords and content structure entered by the user. The server receives a list of relevant files returned as search results. The server downloads the necessary files based on the list. In this step, the keywords and content structure are input, and the list of relevant files and downloaded materials are generated as output.

[1076] Step 4:

[1077] Data analysis and processing

[1078] The server provides the downloaded materials to a generative AI model (e.g., OpenAI GPT-4). The generative AI model analyzes the materials and extracts key points. This extracted information is then organized by the server in accordance with the proposal structure. In this step, the downloaded materials are used as input, and the extracted key points and organized data are generated as output.

[1079] Step 5:

[1080] Presentation generation process

[1081] The server launches the presentation creation software (e.g., Microsoft PowerPoint API, Google Slides API). The server issues a command to create a new presentation file. The server sends the key points extracted by the generative AI model to the presentation creation software. The presentation creation software automatically generates slides corresponding to each section. The generated slides are saved as a single presentation file. The server checks the location where the completed presentation file is saved. In this step, the input is organized data, and the output is a presentation file.

[1082] Step 6:

[1083] User notification and confirmation process

[1084] The server notifies the device of a link to the generated presentation file. The device displays the notified link to the user. The user clicks the link and checks the generated proposal. If necessary, the user can make corrections to the presentation using the device. The user checks the final proposal and submits it to the client or other relevant parties. In this step, the input is a link to the generated presentation file, and the output is the user checking and correcting the proposal.

[1085] The above is the flow of specific processing steps of the program of this system.

[1086] (Application example 1)

[1087] 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."

[1088] In conventional proposal creation systems, the process of users entering detailed information, collecting relevant materials, and then creating a proposal based on that information is time-consuming and labor-intensive. Furthermore, when proposing and explaining products in a virtual store, it is difficult to effectively suggest related products based on the user's interests and purchasing history. To solve these issues, a system is needed that can both streamline the proposal creation process and effectively propose products in a virtual store.

[1089] 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.

[1090] In this invention, the server includes means for a user to input the structure and detailed contents of a proposal, means for searching and retrieving related materials from a storage service, means for analyzing the retrieved materials using a generative AI model to extract key points, means for automatically generating a presentation file based on the extracted key points, means for notifying the user of a link to the generated presentation file, and means for making product suggestions in a virtual store based on the user's interests and purchase history. This allows users to efficiently create high-quality proposals, and also enables the virtual store to make product suggestions optimized for individual users.

[1091] "User" means a person or legal entity who uses this system to input the structure and details of a proposal and receives the generated presentation file.

[1092] A "proposal" is a document in which a user organizes information and summarizes the proposal for a specific purpose or project.

[1093] "Structure" refers to the layout and order of how each element and chapter of the proposal is arranged and organized.

[1094] "Detailed content" refers to the specific service content, product specifications, strategy, objectives, etc. included in the proposal.

[1095] "Storage service" is a general term for online services such as cloud storage and databases that allow you to store, share, and search for information.

[1096] A "generative AI model" is a system that uses artificial intelligence to automatically extract key points from input information and generate texts and presentations.

[1097] A "presentation file" is a slide-format file created to convey specific information in a visually easy-to-understand manner.

[1098] "Link" means the URL or path provided to a user to access the generated presentation file.

[1099] "Virtual store" refers to a virtual shopping environment that exists on the Internet, where users can browse and purchase products online.

[1100] An "interest" is when a user expresses interest in a particular category or product.

[1101] "Purchase history" is a record of products and services a user has purchased in the past.

[1102] The present invention is a system that automatically creates proposals by collecting related materials from a storage service when a user inputs the structure and details of the proposal. This system is composed of multiple means that work together to efficiently generate proposals. The system includes means for accepting user input, means for collecting information, means for analyzing materials, means for generating presentation files, and means for notifying the user of the generated files. In addition, in a virtual store, it also includes means for suggesting products based on the user's interests and purchasing history.

[1103] Program processing explanation

[1104] First, the user logs in to the system from the terminal. The terminal sends the user's login information (user name and password) to the server, and the server authenticates the user using the authentication method. If the authentication is successful, the user is redirected to their dashboard. Next, to create a new proposal, the user enters the proposal configuration and detailed service content. The terminal sends this information to the server.

[1105] The server searches for relevant materials through the storage service's API based on the keywords and content structure entered by the user. A list of relevant files is returned to the server from the storage service as a search result. The server receives the list and downloads the necessary files. The downloaded materials are provided to the generative AI model, which the server activates to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. The server organizes this extracted information based on the proposal structure.

[1106] Next, the server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which automatically generates slides corresponding to each section. The generated slides are saved as a single presentation file. The server then checks the location where the completed presentation file is saved and notifies the user of the access link.

[1107] As a concrete example, user "user123" inputs detailed information about a "new smartphone." The system collects past related reports and automatically generates a presentation as a proposal. The user is notified by email and can view the generated presentation file by clicking the download link. For example, the prompt text the user inputs might look like this:

[1108] "Collecting information to develop proposals for new smartphones, high-resolution cameras, and long-lasting batteries."

[1109] This system allows users to efficiently create high-quality proposals, and also makes it possible to propose products optimized for individual users in virtual stores.

[1110] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1111] Step 1:

[1112] A user logs into the system from a terminal. The terminal sends the user's login information (username and password) to the server. The server authenticates the user using an authentication method. If authentication is successful, the server redirects the user to the user dashboard. The inputs are the username and password, and the output returns whether the user authentication was successful or not.

[1113] Step 2:

[1114] To create a new proposal, a user inputs the proposal structure and detailed service content from their device. This information is sent from the device to the server. The server receives this input data and starts the proposal creation process. The inputs include the proposal structure and details, and the output is saved on the server.

[1115] Step 3:

[1116] The server searches for related materials based on the keywords and content structure entered by the user through the storage service's API. The server receives a list of related files from the storage service. The input is the keywords and content structure entered by the user, and the output is a list of related materials.

[1117] Step 4:

[1118] The server receives the list of relevant documents and downloads the necessary files. The downloaded documents are stored in the server. The input is the list of documents, and the output is the downloaded files.

[1119] Step 5:

[1120] The downloaded materials are provided to the generative AI model. The server runs the generative AI model to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. The downloaded materials are the input, and the extracted key points are the output.

[1121] Step 6:

[1122] The server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which then automatically generates slides corresponding to each section. The extracted key points are the input, and the presentation file is generated as the output.

[1123] Step 7:

[1124] The server checks the location of the generated presentation file and notifies the user of the access link. The user can access the provided link from their device and view the generated proposal. The input is the generated presentation file, and the output is the link notified to the user.

[1125] Step 8:

[1126] In the virtual store, product suggestions are made based on the user's interests and purchase history. The server collects related product information based on the user's input data and purchase history, and provides it as a proposal. The input is the user's interests and purchase history, and the output is the optimal product suggestion.

[1127] 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.

[1128] The present invention is a system that combines an emotion engine when a user inputs the structure and content of a proposal, thereby improving the proposal creation process efficiently and effectively.

[1129] A natural language explanation of the program's processing

[1130] 1. User Input Processing

[1131] First, the user logs in to the system from their terminal. The terminal sends the user's login information to the server, and the server authenticates the user using an authentication method. If authentication is successful, the server sends an instruction to the terminal to redirect to the user's dashboard. To create a new proposal, the user enters the proposal structure and detailed content. The terminal then sends this information to the server.

[1132] 2. Information Collection and Processing

[1133] The server calls the storage service's API to search for and retrieve relevant materials based on the information entered by the user. The storage service returns a list of relevant files to the server, and the server downloads the necessary files.

[1134] 3. Emotion Engine Processing

[1135] As the user enters information, the device's built-in emotion engine recognizes the user's emotions in real time. For example, if the user feels stressed, the emotion engine will send that information to the server, and the system will automatically adjust the interface and assistance functions based on the user's emotions.

[1136] 4. Data analysis and processing

[1137] The downloaded materials are provided to the generative AI model, which is then run by the server to analyze the materials. The generative AI model analyzes the provided materials and extracts key points and important information. The extracted information is then organized by the server into sections of the proposal.

[1138] 5. Presentation Generation Process

[1139] The server launches the presentation creation software and instructs it to create a new presentation file. The key points summarized by the generative AI model are sent to the presentation creation software, which automatically generates slides corresponding to each section. The slides are saved as a single presentation file, and the server generates a link to the file and notifies the user.

[1140] 6. User Notification and Confirmation

[1141] The server sends a link to the generated presentation file to the device. The user accesses the link provided on the device and checks the generated proposal. The user can then revise the presentation content as necessary and check the final proposal.

[1142] Specific examples

[1143] As a specific example, consider a marketer at an advertising agency creating a proposal for a new social media marketing campaign. The user logs in to the system and begins creating a new proposal. The user enters details such as an overview of the service, target market, strategy, and budget. The emotion engine recognizes the user's emotions, and if the user is feeling stressed, for example, the server provides assistance to help the user relax. The server collects past success stories and marketing reports from a storage service, and a generative AI model summarizes the key points. The automatically generated presentation file is notified to the user, who can review it via a link and make any necessary revisions. Ultimately, a high-quality proposal is completed quickly and efficiently.

[1144] This system makes it possible to create high-quality proposals efficiently and quickly while taking into account the user's emotions.

[1145] The processing flow will be explained below.

[1146] Step 1:

[1147] A user logs in to the system from a terminal. The user enters a username and password on the login screen and presses the send button. The terminal sends this information to the server.

[1148] Step 2:

[1149] The server compares the received user information with the database and performs authentication. If authentication is successful, the server sends an instruction to the device to redirect to the user's dashboard.

[1150] Step 3:

[1151] The user clicks the "Create a new proposal" button on the dashboard, which opens a form on the device for entering the proposal structure and service details.

[1152] Step 4:

[1153] The user enters the proposal structure (e.g., objectives, target market, strategy, budget) and detailed service content. After the user has entered all the items, they press the send button. The terminal sends the input information to the server.

[1154] Step 5:

[1155] The server analyzes the received user input information and calls the storage service API to send a request to search for related materials.

[1156] Step 6:

[1157] The storage service returns a list of related files to the server, which then receives the list and downloads the necessary files.

[1158] Step 7:

[1159] As the user enters information, the device's built-in emotion engine recognizes the user's emotions in real time. For example, if the user is feeling stressed, the emotion engine will send that information to the server.

[1160] Step 8:

[1161] Based on the emotional information received by the server, the interface and assistance functions are automatically adjusted, and messages and guidelines are displayed to help the user relax.

[1162] Step 9:

[1163] The server provides the downloaded materials to the generative AI model, which then analyzes the materials and extracts key points and important information.

[1164] Step 10:

[1165] The generative AI model returns the extracted information to the server, which organizes it into sections of the proposal and determines the slide summaries for each section.

[1166] Step 11:

[1167] The server starts the presentation creation software, instructs it to create a new presentation file, and sends specific summaries for each slide to the presentation creation software.

[1168] Step 12:

[1169] The presentation software automatically generates slides and saves the completed slides as a single presentation file. The server confirms the location and link of the generated presentation file.

[1170] Step 13:

[1171] The server notifies the device of the link to the generated presentation file, and the device displays the notification to the user, who can click the link to view the generated proposal.

[1172] Step 14:

[1173] The user accesses the provided link on their device to view the generated proposal, revise the presentation content as needed, and review the final proposal.

[1174] This allows users to quickly and efficiently create high-quality proposals while taking their emotional state into account.

[1175] Example 2

[1176] 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."

[1177] Conventional proposal creation systems have the problem that users have to manually input the structure and details of the proposal, collect related materials, and summarize the main points, which takes a lot of time and effort.In addition, because the system does not take into account the user's emotions, the work often becomes stressful, which can ultimately affect the quality of the proposal.

[1178] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for the user to input the structure and detailed contents of the proposal, a means for recognizing the user's emotions in real time and adjusting the interface and assistance functions based on the emotion data, a means for searching and acquiring related materials from a storage service, a means for analyzing the acquired materials using a generative AI model and extracting key points, a means for automatically generating a presentation file based on the extracted key points, and a means for notifying the user of a link to the generated presentation file. This makes it possible to streamline the proposal creation process and quickly create high-quality proposals while taking user emotions into consideration.

[1179] A "proposal" is a document in which a user organizes and details information, plans, strategies, budgets, etc. regarding a specific idea, project, service or product.

[1180] "Storage service" means an online platform or system used to store, access, and manage data. Examples include cloud storage services.

[1181] A "generative AI model" is an algorithm or system that uses artificial intelligence techniques to analyze and generate data, typically for tasks such as natural language processing and image generation.

[1182] "Recognizing user emotions in real time" refers to technology that analyzes facial expressions, tone of voice, etc. in real time when an end user interacts with a system, and grasps the user's emotional state.

[1183] "Adjusting the interface and assistance functions" means dynamically changing the screen display of the system used by the user and the assistance functions provided in response to the user's emotional state.

[1184] A "presentation file" is an electronic document for visually structuring and presenting information, and is generally structured in slide format.

[1185] "Auto-generate" means that the system automatically performs a specified task (e.g., creating a presentation) based on input data and settings, with little or no manual user interaction.

[1186] "Providing a link" means communicating to the user the URL of the generated file or information in a format that the user can access.

[1187] The present invention is a system that automatically generates high-quality proposals by allowing users to input the structure and content of the proposal while taking into account changes in emotions during the process. This system provides users with a means to create proposals efficiently and effectively.

[1188] This system includes three main components: a server, a terminal, and a user. The specific processing will be explained below.

[1189] First, a user logs in to the system from a terminal. At this time, the terminal sends login information (user name and password) to the server, and the server performs secure user authentication using an authentication method (e.g., OAuth or JWT). If authentication is successful, the user is redirected to a dedicated dashboard.

[1190] To create a new proposal, the user inputs the structure and details of the proposal into the terminal. The terminal sends this input information to the server, which stores the received information in a database.

[1191] Next, the server calls the API of the storage service (e.g., Google Drive or Dropbox) to search for and retrieve materials related to the content entered by the user, and downloads the necessary files based on the file list returned by the storage service.

[1192] During the data entry process, the device's built-in emotion engine (such as Affectiva or IBM Watson Tone Analyzer) recognizes the user's emotions in real time. Emotional data is sent to the server, and if the user is feeling stressed, appropriate assistance functions (such as playing relaxing music or changing the interface) are provided.

[1193] The server inputs the downloaded materials into a generative AI model (e.g., OpenAI's GPT-4) and begins analyzing the materials. The generative AI model extracts key points and important information from the provided materials, and these key points are stored in a database.

[1194] The server then calls the API of the presentation creation software (e.g., Microsoft PowerPoint or Google Slides) to automatically generate a new presentation file based on the extracted key points. The generated presentation file is saved and a link to it is sent to the user.

[1195] The user accesses the link provided on their device, checks the content they entered and the presentation file generated by the system, and, if necessary, makes corrections using the online editing function before confirming and finalizing the proposal.

[1196] (Example)

[1197] Consider a case where a marketing professional at an advertising agency is creating a proposal for a new social media marketing campaign. The professional logs in to the system and clicks the "Create a New Proposal" button. They then enter details such as the target market, strategy, and budget. As they enter their information, an emotion engine recognizes the professional's emotions and notifies the server that they are under stress. While relaxing background music plays, the server collects past success stories from a storage service, and a generative AI model summarizes the key points. A presentation file is automatically generated, and a link is sent to the professional. The professional can review the presentation via the link and make any necessary revisions. This specific example demonstrates how proposal creation can be done quickly and efficiently.

[1198] (Example of a prompt)

[1199] 1. Enter the information required to create a proposal (e.g., service overview, target market, strategy, budget).

[1200] 2. Please explain in detail how the Emotion Engine recognizes the user's emotions and assists them when their stress level is high.

[1201] 3. Please explain in detail the process by which the generative AI model extracts key points from the provided materials.

[1202] 4. Please describe in natural language the process of generating a presentation file and notifying the user.

[1203] The above is an embodiment of the invention.

[1204] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1205] Step 1:

[1206] A user logs in to the system from a terminal. The user enters a username and password on the login page and clicks the login button. The terminal sends the entered authentication information (username and password) to the server. The server performs authentication using an authentication method (for example, OAuth or JWT) and compares it with the user information stored in the database. If authentication is successful, the server sends the URL of the user's dashboard page to the terminal, and the terminal redirects to this page.

[1207] Input: Username, Password

[1208] Data processing: The server searches the database and collates user information

[1209] Output: Dashboard URL upon successful authentication

[1210] Step 2:

[1211] The user clicks the "Create a new proposal" button on the dashboard to display an input screen for creating a new proposal. The user enters detailed information for each section of the proposal (e.g., service overview, target market, strategy, budget). The device sends this input information to the server, which then stores the received information in a database.

[1212] Input: Proposal structure and details

[1213] Data processing: Save to database

[1214] Output: Proposal input confirmation message

[1215] Step 3:

[1216] The server calls the API of the storage service (e.g., Google Drive, Dropbox) and searches for relevant materials based on the proposal details entered by the user. It then downloads the necessary files based on the file list returned by the storage service. The server then obtains the URL of the relevant materials.

[1217] Input: Proposal content entered by the user

[1218] Data processing: Calling the storage service API, obtaining the file list, and downloading

[1219] Output: URL of related material

[1220] Step 4:

[1221] While the user is entering the contents of a document or proposal, the device's built-in emotion engine (e.g., Affectiva, IBM Watson Tone Analyzer) analyzes the user's facial expressions and vocal tone in real time. The recognized emotion data is sent to the server, and if it determines that the user is feeling stressed, the server adjusts the interface and assistance functions. Specifically, it plays relaxing music or changes the color tone of the interface.

[1222] Input: User facial expressions and tone of voice

[1223] Data processing: Analysis by emotion engine and sending emotion data

[1224] Output: Optimized interface and assistance functions

[1225] Step 5:

[1226] The server provides the downloaded materials to a generative AI model (e.g., OpenAI's GPT-4) and begins analyzing the materials. The generative AI model extracts key points and important information from the provided materials. The extracted key points are stored in a database.

[1227] Input: Downloaded materials

[1228] Data processing: Analyzing data and extracting key points using generative AI models

[1229] Output: Extracted key information

[1230] Step 6:

[1231] The server launches presentation creation software (e.g., Google Slides API) and instructs it to create a new presentation file. Slides corresponding to each section are automatically generated based on key point information extracted from the generative AI model. The design and layout of the slides are automatically adjusted. The created presentation file is saved in storage, and a link to it is generated.

[1232] Input: Extracted gist information

[1233] Data processing: API call for presentation creation software and slide generation

[1234] Output: Presentation file link

[1235] Step 7:

[1236] The link to the generated presentation file is sent to the device. The user accesses the provided link on the device, checks the contents of the generated proposal, and, if necessary, uses the online editing function to make corrections and complete the final proposal.

[1237] Input: Presentation file link

[1238] Data processing: Link notification and file access

[1239] Output: Final proposal with online editing functionality

[1240] This completes the processing flow of this system. This series of processing steps enables users to create high-quality proposals efficiently and effectively.

[1241] (Application example 2)

[1242] 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."

[1243] Conventional proposal creation systems required users to manually collect and analyze a huge amount of data, which required a great deal of time and effort. Furthermore, the cumbersome process made users feel stressed, and the quality of the proposals created varied. Since factory and on-site workers are particularly required to create documents quickly and with high quality, improvements were needed to both improve efficiency and reduce stress.

[1244] 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.

[1245] In this invention, the server includes: means for a user to input the structure and detailed contents of a proposal; means for searching and retrieving related materials from a storage service; means for analyzing the retrieved materials using a generative AI model to extract key points; means for notifying the user of a link to the generated presentation file; and means including an emotion engine for recognizing the user's emotions in real time and automatically adjusting the system's interface and assistance functions based on those emotions. This enables the user to efficiently create high-quality proposals, and the emotion engine allows the user to work while reducing stress.

[1246] A "Proposal" is a document in which a User proposes a specific project or idea.

[1247] "Structure" refers to the way in which each section and content in a proposal is organized.

[1248] "Details" refer to the specific information and data that will be included in each section of the proposal.

[1249] "Storage Services" means cloud-based data storage services that allow documents and other data to be stored and accessed as needed.

[1250] "Document search" is the process of searching for and retrieving relevant documents and information needed to prepare a proposal.

[1251] A "generative AI model" is an artificial intelligence model used to analyze provided data and extract key points.

[1252] "Key points extraction" is the process of extracting important points and summaries from documents or information.

[1253] A "presentation file" is a digital file that visually represents the contents of the proposal in an easy-to-understand manner.

[1254] "Link notification" is the process of informing users of the access link for the generated presentation file.

[1255] The "emotion engine" is an engine that analyzes user emotions in real time and adjusts the system's behavior based on the results.

[1256] This invention is a system for making the proposal creation process efficient and effective, automatically generating proposals based on user-provided information using a cloud-based storage service and artificial intelligence (AI) models. It also includes an emotion engine that recognizes user emotions in real time and adjusts the system's interface and support functions based on those emotions.

[1257] Program processing overview

[1258] First, a user logs in from a device (e.g., smart glasses or a PC). At this time, the login information is sent to the server, and the server authenticates the user using an authentication method. If authentication is successful, the user is redirected to the dashboard and can start creating a new proposal.

[1259] When the user enters the structure and details of the proposal, the device sends this information to the server, which then searches for and retrieves relevant materials from a cloud-based storage service. At this point, the Emotion Engine analyzes the user's emotions in real time and provides a relaxation assistance function if it detects stress or fatigue.

[1260] The acquired materials are provided to a generative AI model on the server, which analyzes the materials and extracts key points. The extracted key points are then provided to presentation creation software, which automatically generates a presentation file. This presentation file is then stored in cloud storage, and the user is notified of its access link.

[1261] Specific examples

[1262] Suppose a worker in a factory uses smart glasses to create a maintenance manual for a new machine. The worker verbally inputs the work procedure and important points through the smart glasses. For example, the worker might input a prompt such as, "Create a maintenance manual for a new machine. Steps: 1. Turn off the power. 2. Remove the cover. 3. Replace part A. Important note: Be sure to check the safety devices." EmotionEngine detects that the worker is tired and suggests taking a short break. The generative AI model then analyzes this information and automatically generates a detailed maintenance manual.

[1263] As another example, when creating a work instruction proposing improvements to the efficiency of the manufacturing process to solve the problem of slow production speed, the user would enter, "Create a proposal for improving the efficiency of the manufacturing process. Current problem: slow production speed. Proposed solution: introduce automated equipment. See past success stories." If the worker shows high stress levels, the emotion engine will support the creation of the work instruction by suggesting relaxation techniques, and the AI ​​will analyze the materials and automatically generate the optimal proposal.

[1264] In this way, it is possible to reduce the burden on the user and create proposals quickly and with high quality.

[1265] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1266] Step 1:

[1267] User authentication

[1268] The user enters their login information on their device. The device sends the login information to the server, which then authenticates them. During this authentication process, the server checks the user information against its database to determine if authentication is successful. If authentication is successful, the session begins and the user is redirected to the dashboard.

[1269] Input: User login information

[1270] Output: Authentication result and dashboard screen

[1271] Step 2:

[1272] Enter the proposal details

[1273] The user inputs the structure and details of a new proposal on the device. The device sends this information to the server. The user then inputs the desired components using voice or text input.

[1274] Input: Proposal structure and details

[1275] Output: Proposal information sent to the server

[1276] Step 3:

[1277] Search for related materials

[1278] The server calls the storage service's API, searches for and retrieves related materials based on the proposal content entered by the user, specifically searching for related materials such as past proposals and references, and retrieves a list of them. The server then downloads the necessary files.

[1279] Input: Proposal Information

[1280] Output: Related documents list and downloaded documents

[1281] Step 4:

[1282] emotion recognition

[1283] While the user is entering their proposal, the device's built-in emotion engine recognizes their emotions in real time. The emotion engine analyzes their facial expressions and vocal tone to determine whether they are feeling stressed. If stress levels are high, the server provides assistance to encourage the user to relax.

[1284] Input: User's facial expression, voice tone

[1285] Output: User's emotional state, relaxation assist function

[1286] Step 5:

[1287] Data analysis and key points extraction

[1288] The server provides the downloaded materials to a generative AI model, which then analyzes the materials and extracts key points. The AI ​​model then analyzes the text content of the materials to detect and extract key points.

[1289] Input: Downloaded materials

[1290] Output: Extracted gist

[1291] Step 6:

[1292] Generate presentation files

[1293] The server launches the presentation creation software and automatically creates a presentation file based on the key points extracted by the generative AI model. The created file is saved in cloud storage and an access link is generated.

[1294] Input: Extracted gist

[1295] Output: Auto-generated presentation file, access link

[1296] Step 7:

[1297] User Notification

[1298] The server sends an access link for the generated presentation file to the terminal. The user accesses the provided link on the terminal and checks the generated proposal. If necessary, the user can revise the presentation content and make a final check.

[1299] Input: Access Link

[1300] Output: Proposal review and revision

[1301] In this way, the workload on the user is reduced and proposals can be created quickly and with high quality.

[1302] 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.

[1303] 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.

[1304] 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.

[1305] 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.

[1306] 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.

[1307] 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.

[1308] 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).

[1309] 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.

[1310] 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."

[1311] 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.

[1312] 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).

[1313] 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.

[1314] 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.

[1315] 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.

[1316] 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.

[1317] 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.

[1318] 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.

[1319] 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.

[1320] 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.

[1321] 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.

[1322] 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.

[1323] The following is further disclosed regarding the above embodiment.

[1324] (Claim 1)

[1325] A means for users to input the structure and details of the proposal;

[1326] means for searching and retrieving relevant materials from the storage service;

[1327] A means of analyzing the acquired materials using a generative AI model and extracting key points;

[1328] A means to automatically generate a presentation file based on the extracted key points,

[1329] a means for notifying the user of a link to the generated presentation file;

[1330] A system including:

[1331] (Claim 2)

[1332] 2. The system according to claim 1, wherein the authentication means authenticates the user and redirects the user to a user dashboard upon successful authentication.

[1333] (Claim 3)

[1334] 2. The system according to claim 1, further comprising means for generating a presentation file using presentation creation software and saving the presentation file.

[1335] "Example 1"

[1336] (Claim 1)

[1337] A means for users to input the structure and details of the proposal;

[1338] means for searching and retrieving relevant materials from a data storage device;

[1339] A means for analyzing the acquired materials using an artificial intelligence model and extracting key points;

[1340] A means to automatically generate presentation files based on the extracted key points,

[1341] A means for notifying users of the link to the generated presentation file;

[1342] A means for users to review the generated proposal via a link and make corrections if necessary;

[1343] A system including:

[1344] (Claim 2)

[1345] 2. The system according to claim 1, wherein the authentication means authenticates the user and redirects the user to a user dashboard upon successful authentication.

[1346] (Claim 3)

[1347] 2. The system according to claim 1, further comprising means for generating a presentation material file using presentation material creation software and saving the presentation material file.

[1348] "Application Example 1"

[1349] (Claim 1)

[1350] A means for users to input the structure and details of the proposal;

[1351] means for searching and retrieving relevant materials from the storage service;

[1352] A means of analyzing the acquired materials using a generative AI model and extracting key points;

[1353] A means to automatically generate a presentation file based on the extracted key points,

[1354] a means for notifying the user of a link to the generated presentation file;

[1355] A means for suggesting products based on the user's interests and purchase history in a virtual store;

[1356] A system including:

[1357] (Claim 2)

[1358] 2. The system according to claim 1, wherein the authentication means authenticates the user and redirects the user to a user dashboard upon successful authentication.

[1359] (Claim 3)

[1360] 2. The system according to claim 1, further comprising means for generating a presentation file using presentation creation software and saving the presentation file.

[1361] "Example 2: Combining Emotion Engines"

[1362] (Claim 1)

[1363] A means for users to input the structure and details of the proposal;

[1364] A means to recognize user emotions in real time and adjust the interface and assistance functions based on the emotional data.

[1365] means for searching and retrieving relevant materials from the storage service;

[1366] A means of analyzing the acquired materials using a generative AI model and extracting key points;

[1367] A means to automatically generate a presentation file based on the extracted key points,

[1368] a means for notifying the user of a link to the generated presentation file;

[1369] A system including:

[1370] (Claim 2)

[1371] 2. The system according to claim 1, wherein the authentication means authenticates the user and redirects the user to a user dashboard upon successful authentication.

[1372] (Claim 3)

[1373] 2. The system according to claim 1, further comprising means for generating a presentation file using presentation creation software and saving the presentation file.

[1374] "Application example 2 when combining emotion engines"

[1375] (Claim 1)

[1376] A means for users to input the structure and details of the proposal;

[1377] means for searching and retrieving relevant materials from the storage service;

[1378] A means of analyzing the acquired materials using a generative AI model and extracting key points;

[1379] A means to automatically generate a presentation file based on the extracted key points,

[1380] a means for notifying the user of a link to the generated presentation file;

[1381] means including an emotion engine for recognizing a user's emotion in real time and automatically adjusting the system's interface and assistance functions based on the emotion;

[1382] A system including:

[1383] (Claim 2)

[1384] 2. The system according to claim 1, wherein the authentication means authenticates the user and redirects the user to a user dashboard upon successful authentication.

[1385] (Claim 3)

[1386] 2. The system according to claim 1, further comprising means for generating a presentation file using presentation creation software and saving the presentation file. [Explanation of symbols]

[1387] 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 users to input the structure and details of the proposal; means for searching and retrieving relevant materials from the storage service; A means of analyzing the acquired materials using a generative AI model and extracting key points; A means to automatically generate a presentation file based on the extracted key points, a means for notifying the user of a link to the generated presentation file; A system including:

2. 2. The system according to claim 1, wherein the authentication means authenticates the user, and redirects the user to a user dashboard when the authentication is successful.

3. 2. The system according to claim 1, further comprising means for generating a presentation file using presentation creation software and saving the presentation file.

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