system

Abstract

We provide the system. [Solution] An input means for receiving user input, An analysis means for analyzing the information received by the input means, A search method that searches a database and retrieves similar project information, A means for providing project information obtained by the search means to the user, A means of communication to contact the person in charge of past projects, A means of updating the database by receiving user feedback, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] When launching a new project in a large enterprise, due to the existence of a huge number of stakeholders and a complex organizational structure, it is difficult to accumulate the necessary knowledge and experience, and there is a problem that the project execution speed decreases. In conventional project management tools, the extraction of specific and useful findings from past cases and the efficient access to members involved in the project are limited, and there is a particular lack of knowledge management specialized for large enterprises. Therefore, there is a need for means to effectively utilize past knowledge in order to improve the success rate of projects.

Means for Solving the Problems

[0005] This invention provides a system that allows users to input information about a new project, retrieve similar past project examples from a database, and provide insights based on this information. Specifically, it includes an input means for receiving user input, a search means for acquiring similar past project information, and a provision means for providing this information to the user. Furthermore, it includes a communication means for contacting personnel involved in past projects and an update means for receiving user feedback and updating the database. This method makes it possible to advance projects quickly and efficiently, even in the complex organizational structures of large corporations.

[0006] "User input" refers to data and information provided by users within the system, including details related to new projects.

[0007] "Input means" refers to an interface or mechanism for receiving information from a user, and is a device or method through which the project outline and objectives are input into the system.

[0008] "Analysis means" refers to a device or method used to understand and assign meaning to input data, and is used for classifying project information and recognizing patterns.

[0009] A "search tool" is a device or method for finding relevant information or past cases from a database, and for quickly identifying similar projects.

[0010] A "database" is a collection of information that is systematically stored and made searchable and retrievable, and is used to preserve project history and knowledge.

[0011] "Means of provision" refers to devices or methods for presenting information obtained through search and analysis to users, and for preparing necessary insights so that users can utilize them.

[0012] "Communication means" refers to an interface or mechanism for exchanging information between different systems or devices, enabling contact with past project personnel.

[0013] "Update means" refers to devices or methods for revising the contents of a system or database based on new information or feedback, thereby keeping the knowledge base up to date. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Embodiment 2 when the emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when the emotion engine is combined.

Mode for Carrying Out the Invention

[0015] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), and the like.

[0018] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention provides a knowledge management system that supports the efficient execution of new projects in large corporations. The system is designed to allow users to input project-related information, thereby effectively leveraging insights gained from similar past projects.

[0036] Specifically, when a user enters project details using their device, that data is sent to the server. The server searches its database based on the received information and extracts similar project examples. In this process, generative AI is used to perform advanced pattern recognition and efficiently find relevant data based on the characteristics of the project.

[0037] The server then organizes the acquired data and formats it for user presentation. The terminal displays this data, providing the user with insights including relevant outputs such as presentation materials and Excel files. Furthermore, the user can access an interface through the terminal that allows them to contact past project stakeholders. This enables them to directly obtain specific advice and experience-based insights.

[0038] Furthermore, user feedback is sent to the server via the device, and the server updates its database based on this feedback, ensuring that the information is always up-to-date. This process makes it possible to provide more accurate information for similar projects in the future.

[0039] As a concrete example, imagine a user planning a marketing project for a new product accessing the system and entering project information. In this case, the server identifies marketing strategies for similar products that have been successful in the past and provides relevant materials and data. This allows the user to explore approaches to optimize their own project while referring to past success stories.

[0040] Thus, the system of the present invention can support the launch of new projects and increase their success rate, even in the complex organizational structures of large corporations.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The user uses their device to enter information about the new project. This includes a project overview, the industry involved, and the target deliverables.

[0044] Step 2:

[0045] The terminal sends information entered by the user to the server. The data is appropriately formatted and may be sent in JSON format or other formats.

[0046] Step 3:

[0047] The server analyzes the received project information and prepares to search the database based on that information. This analysis includes extracting topics and keywords from the information.

[0048] Step 4:

[0049] The server searches the database for similar past projects. This search uses generative AI and pattern matching algorithms to identify cases that most closely resemble the project's characteristics.

[0050] Step 5:

[0051] The server extracts relevant knowledge and output from the search results and selects the information to provide to the user. This includes related documents and files (presentation materials, data sheets, etc.).

[0052] Step 6:

[0053] The server formats the selected information into a user-friendly format and sends it to the terminal. The terminal then displays this information in its user interface.

[0054] Step 7:

[0055] Users can view information provided through their devices and, if necessary, use an interface to contact members who were involved in past projects. This feature allows them to obtain direct advice and opinions.

[0056] Step 8:

[0057] Users input newly acquired knowledge and work feedback into the server via their terminals. This allows the server to update its knowledge base and store the data as useful for future projects.

[0058] (Example 1)

[0059] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0060] The problem that this invention aims to solve is to provide a system that can effectively collect and utilize information to support the efficient execution of new activities in large corporations. Users have difficulty effectively utilizing the knowledge gained from past activities, and there is a problem that they cannot make appropriate judgments or plans quickly.

[0061] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0062] In this invention, the server includes means for receiving user input, means for performing pattern recognition using a generative AI model and efficiently extracting relevant information, and means for receiving user feedback and updating the database. This enables users to make effective decisions and optimize new activities based on past cases.

[0063] "User input" refers to project-related data and information that users provide to the system.

[0064] A "generative AI model" refers to artificial intelligence technology that recognizes patterns from past project data and extracts relevant information.

[0065] A "database" refers to a collection of information that stores records of various project information and is structured for retrieval.

[0066] "Pattern recognition" refers to a technology that automatically detects commonalities and features hidden within data.

[0067] "Feedback" refers to responses and opinions based on the results and evaluations of a project that a user provides to the system.

[0068] "Formatting" refers to processing acquired information into a format that is easy for users to understand and then displaying it.

[0069] "Communication methods" refer to the methods and technologies that users use to contact past project managers.

[0070] Embodiments of the present invention will now be described. The present invention is a system that supports the efficient execution of new activities in large corporations and is composed of collaboration between users, servers, and terminals.

[0071] The user uses a terminal to enter information related to the new activity. This terminal has an interface designed to reliably accept user input, providing screens for entering specific items such as project name, purpose, budget, and deadline. The entered data is securely transmitted to the server in an encrypted format.

[0072] The server searches the database based on the received information and identifies similar past activity data. In this step, a generative AI model is used, employing advanced pattern recognition to efficiently extract relevant information based on the project's characteristics. Next, the server organizes the acquired data and formats it for user presentation. This information is provided in visual formats such as reports and graphs to ensure user understanding.

[0073] The terminal displays information sent from the server, visually presenting information to the user. This allows the user to obtain concrete guidelines for planning and executing new activities by referring to past examples. The terminal is also equipped with communication methods for contacting past project managers, making it easy to obtain specific feedback and advice via email or chat.

[0074] Furthermore, user feedback is sent to the server via the device, and the server updates the database to reflect this feedback, improving search accuracy for subsequent searches.

[0075] As a concrete example, consider a user developing a marketing strategy for a new product. In this case, the user would input a prompt such as, "I am currently formulating a market launch strategy for new product B. What can I learn from past success stories?" and the system would then present past success stories. This process would enable the user to form a concrete strategy to optimize their own activities.

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

[0077] Step 1:

[0078] The user uses a terminal to enter information related to the new activity. The entered data includes items such as project name, purpose, budget, and deadline. This information entered by the user is collected by the terminal as digital data and sent to the server in an encrypted format.

[0079] Step 2:

[0080] Based on the user input received, the server searches the database for similar past activity information. It utilizes the project information obtained as input to perform advanced pattern recognition using a generative AI model. In this process, the server selects relevant projects from past data and extracts related information based on their characteristics.

[0081] Step 3:

[0082] The server organizes and formats data on similar projects retrieved through searches. It organizes the extracted project information as input and formats it into a visually easy-to-understand format for presentations and reports. This formatted data is then output to the user.

[0083] Step 4:

[0084] The terminal receives formatted information sent from the server and displays it to the user. The terminal uses visual tools, such as graphs and charts, to present the information in a way that the user can intuitively understand. This allows the user to develop concrete plans for current activities based on past examples.

[0085] Step 5:

[0086] Users can contact past project managers via their devices. The devices are equipped with communication tools such as email and chat to ask questions and seek advice from managers. This feature allows users to directly access past experience and expertise.

[0087] Step 6:

[0088] User feedback is sent to the server via the terminal. The server verifies the feedback and adds / updates the newly acquired knowledge to the database. This strengthens the system's overall knowledge base and improves the accuracy of future inquiries.

[0089] (Application Example 1)

[0090] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0091] Regarding the efficient execution of new projects on-site, there is a problem in work environments such as factories where it is difficult to refer to past knowledge and case studies in a timely manner. Furthermore, when hands are full or when it is necessary to advance a project quickly, there is a need for more immediate and effective information gathering and processing. Therefore, the present invention aims to provide a system that allows easy real-time access to past project information and utilizes voice control to enable users to quickly obtain information and support their work.

[0092] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0093] In this invention, the server includes an input means for receiving user input, a visualization means for displaying information in real time, and a control means for enabling operation by voice control. This allows users to quickly access necessary information by voice control while visually checking past project information in real time at a factory or other work site.

[0094] "An input method that accepts user input" refers to an interface that allows users to provide information about new projects to the system.

[0095] "Analysis method" refers to a processing method for structuring received user input and identifying project characteristics.

[0096] "Search method" refers to a function that retrieves past project information from a database and extracts similar cases.

[0097] "Means of provision" refers to the means of displaying the searched information in an easy-to-understand manner for the user.

[0098] "Means of communication" refers to methods for contacting personnel involved in past projects.

[0099] "Update methods" refer to methods for receiving user feedback and keeping the database content constantly up-to-date.

[0100] "Visualization means" refers to display technologies for showing project information to users in real time.

[0101] "Control means" refers to an interface for operating the system using voice or other sensory inputs.

[0102] This invention is a system for efficiently executing new projects on a factory floor. The system is designed to allow users to access project information in real time using smart glasses or other wearable devices.

[0103] The server analyzes data received through user input and searches for similar project information in the database. During this process, it uses a generative AI model to perform advanced pattern recognition and extract past cases related to the project.

[0104] The acquired information is displayed on the user's terminal using visualization tools. This allows the user to visually confirm project-specific information. Voice control is also provided, enabling users to easily access and operate the system using voice commands.

[0105] For example, when a factory worker introducing a new painting technique inputs project information, the server can extract data from similar past projects and provide information such as successful paint formulations and temperature settings. This allows the worker to quickly acquire the necessary knowledge and optimize the project.

[0106] An example of a prompt for the generated AI model is: "Search for past project data related to the new painting process. Display related documents in Japanese."

[0107] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0108] Step 1:

[0109] The user inputs information about a new project through smart glasses. This input may include the project name, related keywords, or voice commands. Upon receiving this input, the system obtains the data necessary for the next process.

[0110] Step 2:

[0111] The terminal sends the received input information to the server. The server analyzes the data and structures it to identify project characteristics. In this process, it extracts necessary data attributes and converts the format.

[0112] Step 3:

[0113] The server performs a database search using the analyzed data. By utilizing a generative AI model and performing advanced pattern recognition, it extracts information on similar past projects. This search yields a dataset of related projects.

[0114] Step 4:

[0115] The server displays the extracted information on the user's terminal in real time using visualization tools. The displayed data includes a list of materials used, process steps, and past success stories. At this point, the data is formatted for the user to visually review.

[0116] Step 5:

[0117] Users interact with the displayed information using voice control. Voice commands allow them to navigate to specific data and view details. This enables users to quickly access the information they need and use it to carry out their projects.

[0118] Step 6:

[0119] When a user provides feedback, the device sends it to the server. The server reflects this in the database and updates the information. This update ensures that more accurate data is provided the next time information is searched for in the project.

[0120] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0121] This invention combines a system for efficiently managing knowledge in new projects for large corporations with an emotion engine that recognizes user emotions. The system aims to improve project success rates by not only providing insights from similar past projects based on user input, but also analyzing user emotions through the emotion engine to provide more appropriate support.

[0122] Specifically, first, the user inputs information related to the new project through a terminal. This information is sent to the server, where the project's characteristics and objectives are identified through analysis. The server then searches the database to retrieve information on similar projects. This information is then provided to the user through the user interface.

[0123] Furthermore, the emotion engine analyzes user input (text and voice) to recognize emotions. This emotional information is used to adjust the user interface and provide feedback to the user. For example, if the system detects that a user is feeling anxious about a project, it is designed to boost the user's motivation by presenting past project success stories and encouraging messages.

[0124] As a concrete example, consider a scenario where a user uses this system when launching a new product development project. In this case, the user inputs an overview of the project into a terminal, and simultaneously, the emotion engine recognizes the user's anxieties. This system not only introduces past success stories that are helpful for project progress, but also presents the specific strategies and countermeasures used in those cases. Furthermore, positive feedback and advice from those who were responsible for the successful projects are also provided.

[0125] Through these means, the present invention supports the execution process of prospective projects and contributes to reducing user anxiety and stress. As a result, it becomes possible to efficiently execute new projects and increase the success rate even within the complex organizational structure of large corporations.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] Users use their devices to enter detailed information about a new project. This information includes the project's objectives, target market, and desired outcomes. In addition, comments and opinions from the user may also be entered.

[0129] Step 2:

[0130] The terminal sends the entered information to the server. The transmitted data is structured, and each attribute of the project is appropriately tagged.

[0131] Step 3:

[0132] The server receives the project information and extracts the project's key characteristics using analysis tools. Furthermore, it searches the database based on this information to identify similar past projects.

[0133] Step 4:

[0134] The server organizes data on similar projects extracted from search results. It generates an information set to provide to the user, including relevant documents, deliverables, and success factors.

[0135] Step 5:

[0136] Based on the information entered by the user, the emotion engine analyzes the user's text and voice information to recognize their current emotional state. For example, it may determine that the user is feeling stressed.

[0137] Step 6:

[0138] Based on the analysis results of the emotion engine, the server dynamically adjusts the feedback and advice given to the user. This may include encouraging messages based on success stories and practical advice for stress reduction.

[0139] Step 7:

[0140] The terminal displays information and feedback received from the server in its user interface. Users can view this information and, if necessary, select actions by following the on-screen instructions.

[0141] Step 8:

[0142] Users input insights gained and feedback on project progress into the server via their terminals. The server uses this feedback to update its database and improve the accuracy of future project support.

[0143] (Example 2)

[0144] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0145] In new projects at large corporations, the challenge lies in efficiently leveraging knowledge from past projects and providing support that takes user emotions into consideration, thereby improving the project's success rate. In particular, there is a need to alleviate user anxiety and stress, and to provide accurate information and emotional support.

[0146] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0147] In this invention, the server includes means for receiving information via a user interface, means for analyzing the received information and identifying emotional information, and means for searching for and retrieving the characteristics of similar projects in data storage. This makes it possible to effectively utilize past knowledge related to the project and provide feedback that responds to the user's emotions.

[0148] A "user interface" is an interface through which a user can input information into a system and receive output.

[0149] A "means for receiving information" refers to a means that receives data entered by a user and passes it to a server for processing.

[0150] "Analysis techniques" are technologies used to process received information and extract meaningful information and emotions from data.

[0151] A "means for identifying emotional information" refers to a means that has the function of analyzing and identifying a user's emotional state based on their input.

[0152] "Data storage" refers to a storage device used to store project information and user input data.

[0153] "Methods for searching and obtaining characteristics of similar projects" refers to methods of searching through past projects for those with similar characteristics to the current project and obtaining that information.

[0154] "Means for generating and providing feedback" refers to a method that has the function of creating and presenting responses in a way that is easy for users to understand, based on the data that has been acquired.

[0155] A "means for adjusting feedback" refers to a function that modifies the content and method of feedback according to the user's emotional state and reaction.

[0156] "Means of providing successful strategies" refers to methods for presenting users with effective strategies and methods used in past projects.

[0157] The system of this invention integrates knowledge sharing and sentiment analysis in project management. Users input project-related information using a terminal. The input information is received by a server, which uses analysis means to identify the characteristics of the project and detects the user's emotions using a sentiment analysis engine.

[0158] The server searches the data storage based on the analyzed information to retrieve information on similar past projects. A specific algorithm is used to retrieve this information, selecting projects with high similarity. For example, if the project objectives and required resources are similar, that example will be selected.

[0159] The acquired project information is restructured in a format tailored to the user's needs by a feedback generation system and displayed on the user interface via the terminal. Feedback based on sentiment analysis is also provided, and if the user is feeling anxious, success stories and encouraging messages are presented. This allows users to receive appropriate support and gain knowledge useful for their own projects.

[0160] As a concrete example, consider a scenario where a user uses this system to launch a development plan for a new product. In this case, the user inputs the project overview, goals, market research results, etc., into the terminal. The system analyzes this information and provides guidance to help the project progress based on similar successful cases from the past. Furthermore, if the emotion engine detects the user's anxiety, it provides encouragement and specific advice.

[0161] An example of a prompt to input to a generative AI model would be, "Please provide examples of similar cases and emotional support in a new product development project." This would allow the system to integrate relevant information and provide comprehensive support to the user.

[0162] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0163] Step 1:

[0164] The user uses a terminal to enter the necessary information for a new project. This information includes the project's purpose, goals, required resources, and planned start date. The entered data is sent to the server in a structured format.

[0165] Step 2:

[0166] The server passes the received information to the analysis tool to identify the project's characteristics and objectives. Specifically, it uses natural language processing techniques to extract keywords and themes from the text data and identify the project's category. The structured data obtained through the analysis becomes the input for the next step.

[0167] Step 3:

[0168] The server searches the data storage based on the analysis results to retrieve similar past project information. A specific algorithm is used for the search, selecting examples that match the project's objectives and conditions. The retrieved project information becomes the output of this step.

[0169] Step 4:

[0170] The terminal displays information retrieved from the server in a user interface. This information includes summaries of similar projects, strategies used, and factors contributing to their success. Users can use this information to consider strategies that may be useful for their own projects.

[0171] Step 5:

[0172] The text entered by the user is then sent to an emotion analysis engine, which identifies the user's emotional state. Through computer analysis, emotional nuances are extracted from the text data, detecting emotions such as anxiety, joy, and anticipation. The emotional information becomes the output of this step.

[0173] Step 6:

[0174] The server generates feedback that takes emotional information into account. For example, if the user is feeling anxious, it will generate encouraging messages or positive information from past success stories. The generated feedback is then displayed in the user interface as the final output.

[0175] Step 7:

[0176] The device monitors responses to user feedback and adjusts the content of subsequent feedback as needed. By repeating the feedback cycle until the user is satisfied, it is possible to address user concerns and questions.

[0177] (Application Example 2)

[0178] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0179] Traditional knowledge management systems often fail to address user concerns and questions because they merely provide historical data without considering user emotions. Furthermore, especially in e-commerce, understanding customer emotions and providing appropriate information and support is crucial for improving the customer experience. However, this process is not currently well-implemented, creating a need for a system capable of flexible and effective responses tailored to user emotions.

[0180] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0181] In this invention, the server includes emotion recognition means for analyzing the user's emotions, information presentation means for supporting the project based on the recognized emotions, and information retrieval means for searching a data storage device and obtaining similar work information. This makes it possible to provide past work information based on data entered by the user, while also providing appropriate information and support according to the user's emotional state.

[0182] "User input" refers to the information and data that a user provides to the system.

[0183] "Information input means" refers to devices or programs that have the function of receiving data from users.

[0184] "Information analysis means" refers to devices or programs used to process and analyze received data.

[0185] An "information retrieval means" is a device or program that has the function of searching a data storage device and retrieving related information.

[0186] "Information provision means" refers to devices or programs that have the function of presenting analyzed and retrieved information to the user.

[0187] "Information and communication means" refers to devices and programs used to send and receive data between users and other parties.

[0188] A "data update means" is a device or program that has the function of updating the contents of a data storage device based on new information or user evaluations.

[0189] "Emotion recognition means" refers to devices or programs used to analyze and recognize a user's emotions.

[0190] An "information presentation means" is a device or program that has the function of showing the user appropriate support information in accordance with the results of the emotion recognition means.

[0191] "Data generation means" refers to devices or programs that have the function of organizing and structuring past work information and providing it in a new format.

[0192] This invention comprises a system that effectively supports project progress by analyzing user input and emotional states. The system recognizes emotions from text and voice input by the user via a terminal such as a smartphone or personal computer, and provides appropriate information based on that.

[0193] The terminal receives input information from the user and sends it to the server. The server incorporates information analysis, information retrieval, and emotion recognition capabilities. The information analysis capabilities analyze the input information to identify the characteristics and objectives of the project. The information retrieval capabilities search and retrieve information on similar past projects from the data storage device. Finally, the emotion recognition capabilities use an AI model to determine the user's emotions from the input data.

[0194] For example, when a user inputs project information related to new product development, and their emotions such as tension and anxiety are analyzed, the system presents the user with information on past success stories and encouraging messages. Then, using appropriate information presentation methods, it provides the user with practical advice and strategies based on the analyzed data. This is expected to improve user motivation and reduce anxiety.

[0195] As a concrete example, when a customer purchases a product on an online shop and writes a review, we can consider a prompt that automatically analyzes their emotions and provides information to improve their satisfaction. An example of such a prompt would be, "Analyze the user's emotions from this review and provide appropriate advice." In this way, the system can improve the customer experience and provide better service.

[0196] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0197] Step 1:

[0198] The terminal receives project information from the user as text or voice data. The input data is formatted by the terminal and sent to the server. At this stage, the data entered by the user is collected in its raw state.

[0199] Step 2:

[0200] The server analyzes the received data using information analysis tools. Specifically, it tokenizes text data using natural language processing techniques and extracts project characteristics and objectives. It identifies keywords and context from the input data and prepares it for searching for similar projects in a database. The analyzed information is then supplied to the search tools.

[0201] Step 3:

[0202] The server's information retrieval mechanism searches data storage devices and retrieves information on similar projects. It indexes records within the database and extracts data based on criteria that match the analysis results. The search results include past project success stories and strategies. This information is then passed to the information provision mechanism.

[0203] Step 4:

[0204] The server's emotion recognition system uses a generative AI model to recognize the user's emotions from received text or audio data. It analyzes the emotional nuances of the input data and determines emotional states such as positive, negative, or neutral. The recognized emotion information is then sent to the information presentation system within the server.

[0205] Step 5:

[0206] The server's information presentation method constructs support information for the user based on acquired similar project information and sentiment recognition results. For example, it combines advice based on past success stories with messages to alleviate emotions. This content is sent to the terminal and displayed to the user.

[0207] Step 6:

[0208] User reactions and feedback are sent back to the server via the device. This feedback is recorded and updated in the database by a data update mechanism, and reflected in future system improvements and accuracy enhancements. In this way, the system is continuously improved, enabling the provision of more personalized user support.

[0209] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0210] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0211] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0212] [Second Embodiment]

[0213] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0214] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0215] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0216] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0217] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0218] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0219] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0220] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0221] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0222] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0223] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0224] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0225] This invention provides a knowledge management system that supports the efficient execution of new projects in large corporations. The system is designed to allow users to input project-related information, thereby effectively leveraging insights gained from similar past projects.

[0226] Specifically, when a user enters project details using their device, that data is sent to the server. The server searches its database based on the received information and extracts similar project examples. In this process, generative AI is used to perform advanced pattern recognition and efficiently find relevant data based on the characteristics of the project.

[0227] The server then organizes the acquired data and formats it for user presentation. The terminal displays this data, providing the user with insights including relevant outputs such as presentation materials and Excel files. Furthermore, the user can access an interface through the terminal that allows them to contact past project stakeholders. This enables them to directly obtain specific advice and experience-based insights.

[0228] Furthermore, user feedback is sent to the server via the device, and the server updates its database based on this feedback, ensuring that the information is always up-to-date. This process makes it possible to provide more accurate information for similar projects in the future.

[0229] As a concrete example, imagine a user planning a marketing project for a new product accessing the system and entering project information. In this case, the server identifies marketing strategies for similar products that have been successful in the past and provides relevant materials and data. This allows the user to explore approaches to optimize their own project while referring to past success stories.

[0230] Thus, the system of the present invention can support the launch of new projects and increase their success rate, even in the complex organizational structures of large corporations.

[0231] The following describes the processing flow.

[0232] Step 1:

[0233] The user uses their device to enter information about the new project. This includes a project overview, the industry involved, and the target deliverables.

[0234] Step 2:

[0235] The terminal sends information entered by the user to the server. The data is appropriately formatted and may be sent in JSON format or other formats.

[0236] Step 3:

[0237] The server analyzes the received project information and prepares to search the database based on that information. This analysis includes extracting topics and keywords from the information.

[0238] Step 4:

[0239] The server searches the database for similar past projects. This search uses generative AI and pattern matching algorithms to identify cases that most closely resemble the project's characteristics.

[0240] Step 5:

[0241] The server extracts relevant knowledge and output from the search results and selects the information to provide to the user. This includes related documents and files (presentation materials, data sheets, etc.).

[0242] Step 6:

[0243] The server formats the selected information into a user-friendly format and sends it to the terminal. The terminal then displays this information in its user interface.

[0244] Step 7:

[0245] Users can view information provided through their devices and, if necessary, use an interface to contact members who were involved in past projects. This feature allows them to obtain direct advice and opinions.

[0246] Step 8:

[0247] Users input newly acquired knowledge and work feedback into the server via their terminals. This allows the server to update its knowledge base and store the data as useful for future projects.

[0248] (Example 1)

[0249] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0250] The problem that this invention aims to solve is to provide a system that can effectively collect and utilize information to support the efficient execution of new activities in large corporations. Users have difficulty effectively utilizing the knowledge gained from past activities, and there is a problem that they cannot make appropriate judgments or plans quickly.

[0251] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0252] In this invention, the server includes means for receiving user input, means for performing pattern recognition using a generative AI model and efficiently extracting relevant information, and means for receiving user feedback and updating the database. This enables users to make effective decisions and optimize new activities based on past cases.

[0253] "User input" refers to project-related data and information that users provide to the system.

[0254] A "generative AI model" refers to artificial intelligence technology that recognizes patterns from past project data and extracts relevant information.

[0255] A "database" refers to a collection of information that stores records of various project information and is structured for retrieval.

[0256] "Pattern recognition" refers to a technology that automatically detects commonalities and features hidden within data.

[0257] "Feedback" refers to responses and opinions based on the results and evaluations of a project that a user provides to the system.

[0258] "Formatting" refers to processing acquired information into a format that is easy for users to understand and then displaying it.

[0259] "Communication methods" refer to the methods and technologies that users use to contact past project managers.

[0260] Embodiments of the present invention will now be described. The present invention is a system that supports the efficient execution of new activities in large corporations and is composed of collaboration between users, servers, and terminals.

[0261] The user uses a terminal to enter information related to the new activity. This terminal has an interface designed to reliably accept user input, providing screens for entering specific items such as project name, purpose, budget, and deadline. The entered data is securely transmitted to the server in an encrypted format.

[0262] The server searches the database based on the received information and identifies similar past activity data. In this step, a generative AI model is used, employing advanced pattern recognition to efficiently extract relevant information based on the project's characteristics. Next, the server organizes the acquired data and formats it for user presentation. This information is provided in visual formats such as reports and graphs to ensure user understanding.

[0263] The terminal displays information sent from the server, visually presenting information to the user. This allows the user to obtain concrete guidelines for planning and executing new activities by referring to past examples. The terminal is also equipped with communication methods for contacting past project managers, making it easy to obtain specific feedback and advice via email or chat.

[0264] Furthermore, user feedback is sent to the server via the device, and the server updates the database to reflect this feedback, improving search accuracy for subsequent searches.

[0265] As a concrete example, consider a user developing a marketing strategy for a new product. In this case, the user would input a prompt such as, "I am currently formulating a market launch strategy for new product B. What can I learn from past success stories?" and the system would then present past success stories. This process would enable the user to form a concrete strategy to optimize their own activities.

[0266] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0267] Step 1:

[0268] The user uses a terminal to enter information related to the new activity. The entered data includes items such as project name, purpose, budget, and deadline. This information entered by the user is collected by the terminal as digital data and sent to the server in an encrypted format.

[0269] Step 2:

[0270] Based on the user input received, the server searches the database for similar past activity information. It utilizes the project information obtained as input to perform advanced pattern recognition using a generative AI model. In this process, the server selects relevant projects from past data and extracts related information based on their characteristics.

[0271] Step 3:

[0272] The server organizes and formats data on similar projects retrieved through searches. It organizes the extracted project information as input and formats it into a visually easy-to-understand format for presentations and reports. This formatted data is then output to the user.

[0273] Step 4:

[0274] The terminal receives formatted information sent from the server and displays it to the user. The terminal uses visual tools, such as graphs and charts, to present the information in a way that the user can intuitively understand. This allows the user to develop concrete plans for current activities based on past examples.

[0275] Step 5:

[0276] Users can contact past project managers via their devices. The devices are equipped with communication tools such as email and chat to ask questions and seek advice from managers. This feature allows users to directly access past experience and expertise.

[0277] Step 6:

[0278] Feedback from the user is sent to the server through the terminal. The server verifies the feedback and adds / updates the newly obtained findings to the database. As a result, the overall knowledge base of the system is strengthened, and the accuracy for inquiries after the next time is improved.

[0279] (Application Example 1)

[0280] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as the "server", and the smart glasses 214 are referred to as the "terminal".

[0281] Regarding the efficient execution of new projects at the site, there is a problem that it is difficult to refer to past knowledge and cases in a timely manner in a working environment such as a factory. Also, in situations where the hands are occupied or when it is necessary to proceed with the project quickly, it is required to collect and process information more immediately and effectively. Therefore, the present invention aims to provide a system that can easily access past project information in real time, and by utilizing voice control, enables the user to quickly obtain information and support the work.

[0282] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0283] In this invention, the server includes an input means for receiving user input, a visualization means for visually displaying information in real time, and a control means that can be operated by voice control. As a result, it becomes possible for the user to quickly access the necessary information by voice operation while visually confirming past project information in real time at the site such as a factory.

[0284] The "input means for receiving user input" refers to an interface for the user to provide information related to a new project to the system.

[0285] The "analysis means" refers to a processing method for structuring the received user input and identifying project characteristics.

[0286] The "search means" refers to a function for searching for past project information from a database and extracting similar cases.

[0287] The "provision means" refers to means for presenting the searched information to the user in an understandable manner.

[0288] The "communication means" refers to a method for communicating with the person in charge related to past projects.

[0289] The "update means" refers to a method for receiving feedback from the user and keeping the database content up-to-date at all times.

[0290] The "visualization means" refers to a display technology for presenting project information to the user in real time.

[0291] The "control means" refers to an interface for operating the system using voice or other sensory inputs.

[0292] The present invention is a system for efficiently performing a new project at a factory site. This system is designed so that a user can access project information in real time using smart glasses or other wearable terminals.

[0293] The server analyzes the data received through an input means for receiving user input, and searches for similar project information in the database. At that time, advanced pattern recognition is performed using a generated AI model to extract past cases related to the project.

[0294] The acquired information is displayed on the user's terminal using visualization tools. This allows the user to visually confirm project-specific information. Voice control is also provided, enabling users to easily access and operate the system using voice commands.

[0295] For example, when a factory worker introducing a new painting technique inputs project information, the server can extract data from similar past projects and provide information such as successful paint formulations and temperature settings. This allows the worker to quickly acquire the necessary knowledge and optimize the project.

[0296] An example of a prompt for the generated AI model is: "Search for past project data related to the new painting process. Display related documents in Japanese."

[0297] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0298] Step 1:

[0299] The user inputs information about a new project through smart glasses. This input may include the project name, related keywords, or voice commands. Upon receiving this input, the system obtains the data necessary for the next process.

[0300] Step 2:

[0301] The terminal sends the received input information to the server. The server analyzes the data and structures it to identify project characteristics. In this process, it extracts necessary data attributes and converts the format.

[0302] Step 3:

[0303] The server executes a database search using the analyzed data. By leveraging a generative AI model to perform advanced pattern recognition, it extracts information on similar past projects. This search yields a dataset of relevant projects.

[0304] Step 4:

[0305] The server displays the extracted information in real time on the user's terminal by means of visualization. The data to be displayed includes a list of materials used, process procedures, past success cases, etc. At this point, the data is arranged in a format that allows the user to visually confirm it.

[0306] Step 5:

[0307] The user operates the displayed information using voice control. By means of voice commands, the user can navigate to specific data and check the details. This enables the user to quickly access the necessary information and utilize it for project execution.

[0308] Step 6:

[0309] When the user provides feedback, the terminal sends it to the server. The server reflects this in the database and updates the information. This update provides more accurate data during the next project information search.

[0310] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion recognition model 59 and perform specific processing using the user's emotion.

[0311] This invention combines a system for efficiently managing knowledge in new projects for large corporations with an emotion engine that recognizes user emotions. The system aims to improve project success rates by not only providing insights from similar past projects based on user input, but also analyzing user emotions through the emotion engine to provide more appropriate support.

[0312] Specifically, first, the user inputs information related to the new project through a terminal. This information is sent to the server, where the project's characteristics and objectives are identified through analysis. The server then searches the database to retrieve information on similar projects. This information is then provided to the user through the user interface.

[0313] Furthermore, the emotion engine analyzes user input (text and voice) to recognize emotions. This emotional information is used to adjust the user interface and provide feedback to the user. For example, if the system detects that a user is feeling anxious about a project, it is designed to boost the user's motivation by presenting past project success stories and encouraging messages.

[0314] As a concrete example, consider a scenario where a user uses this system when launching a new product development project. In this case, the user inputs an overview of the project into a terminal, and simultaneously, the emotion engine recognizes the user's anxieties. This system not only introduces past success stories that are helpful for project progress, but also presents the specific strategies and countermeasures used in those cases. Furthermore, positive feedback and advice from those who were responsible for the successful projects are also provided.

[0315] Through these means, the present invention supports the execution process of prospective projects and contributes to reducing user anxiety and stress. As a result, it becomes possible to efficiently execute new projects and increase the success rate even within the complex organizational structure of large corporations.

[0316] The following describes the processing flow.

[0317] Step 1:

[0318] Users use their devices to enter detailed information about a new project. This information includes the project's objectives, target market, and desired outcomes. In addition, comments and opinions from the user may also be entered.

[0319] Step 2:

[0320] The terminal sends the entered information to the server. The transmitted data is structured, and each attribute of the project is appropriately tagged.

[0321] Step 3:

[0322] The server receives the project information and extracts the project's key characteristics using analysis tools. Furthermore, it searches the database based on this information to identify similar past projects.

[0323] Step 4:

[0324] The server organizes data on similar projects extracted from search results. It generates an information set to provide to the user, including relevant documents, deliverables, and success factors.

[0325] Step 5:

[0326] Based on the information entered by the user, the emotion engine analyzes the user's text and voice information to recognize their current emotional state. For example, it may determine that the user is feeling stressed.

[0327] Step 6:

[0328] Based on the analysis results of the emotion engine, the server dynamically adjusts the feedback and advice given to the user. This may include encouraging messages based on success stories and practical advice for stress reduction.

[0329] Step 7:

[0330] The terminal displays information and feedback received from the server in its user interface. Users can view this information and, if necessary, select actions by following the on-screen instructions.

[0331] Step 8:

[0332] Users input insights gained and feedback on project progress into the server via their terminals. The server uses this feedback to update its database and improve the accuracy of future project support.

[0333] (Example 2)

[0334] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0335] In new projects at large corporations, the challenge lies in efficiently leveraging knowledge from past projects and providing support that takes user emotions into consideration, thereby improving the project's success rate. In particular, there is a need to alleviate user anxiety and stress, and to provide accurate information and emotional support.

[0336] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0337] In this invention, the server includes means for receiving information via a user interface, means for analyzing the received information and identifying emotional information, and means for searching for and retrieving the characteristics of similar projects in data storage. This makes it possible to effectively utilize past knowledge related to the project and provide feedback that responds to the user's emotions.

[0338] A "user interface" is an interface through which a user can input information into a system and receive output.

[0339] A "means for receiving information" refers to a means that receives data entered by a user and passes it to a server for processing.

[0340] "Analysis techniques" are technologies used to process received information and extract meaningful information and emotions from data.

[0341] A "means for identifying emotional information" refers to a means that has the function of analyzing and identifying a user's emotional state based on their input.

[0342] "Data storage" refers to a storage device used to store project information and user input data.

[0343] "Methods for searching and obtaining characteristics of similar projects" refers to methods of searching through past projects for those with similar characteristics to the current project and obtaining that information.

[0344] "Means for generating and providing feedback" refers to a method that has the function of creating and presenting responses in a way that is easy for users to understand, based on the data that has been acquired.

[0345] A "means for adjusting feedback" refers to a function that modifies the content and method of feedback according to the user's emotional state and reaction.

[0346] "Means of providing successful strategies" refers to methods for presenting users with effective strategies and methods used in past projects.

[0347] The system of this invention integrates knowledge sharing and sentiment analysis in project management. Users input project-related information using a terminal. The input information is received by a server, which uses analysis means to identify the characteristics of the project and detects the user's emotions using a sentiment analysis engine.

[0348] The server searches the data storage based on the analyzed information to retrieve information on similar past projects. A specific algorithm is used to retrieve this information, selecting projects with high similarity. For example, if the project objectives and required resources are similar, that example will be selected.

[0349] The acquired project information is restructured in a format tailored to the user's needs by a feedback generation system and displayed on the user interface via the terminal. Feedback based on sentiment analysis is also provided, and if the user is feeling anxious, success stories and encouraging messages are presented. This allows users to receive appropriate support and gain knowledge useful for their own projects.

[0350] As a concrete example, consider a scenario where a user uses this system to launch a development plan for a new product. In this case, the user inputs the project overview, goals, market research results, etc., into the terminal. The system analyzes this information and provides guidance to help the project progress based on similar successful cases from the past. Furthermore, if the emotion engine detects the user's anxiety, it provides encouragement and specific advice.

[0351] An example of a prompt to input to a generative AI model would be, "Please provide examples of similar cases and emotional support in a new product development project." This would allow the system to integrate relevant information and provide comprehensive support to the user.

[0352] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0353] Step 1:

[0354] The user uses a terminal to enter the necessary information for a new project. This information includes the project's purpose, goals, required resources, and planned start date. The entered data is sent to the server in a structured format.

[0355] Step 2:

[0356] The server passes the received information to the analysis tool to identify the project's characteristics and objectives. Specifically, it uses natural language processing techniques to extract keywords and themes from the text data and identify the project's category. The structured data obtained through the analysis becomes the input for the next step.

[0357] Step 3:

[0358] The server searches the data storage based on the analysis results to retrieve similar past project information. A specific algorithm is used for the search, selecting examples that match the project's objectives and conditions. The retrieved project information becomes the output of this step.

[0359] Step 4:

[0360] The terminal displays information retrieved from the server in a user interface. This information includes summaries of similar projects, strategies used, and factors contributing to their success. Users can use this information to consider strategies that may be useful for their own projects.

[0361] Step 5:

[0362] The text entered by the user is then sent to an emotion analysis engine, which identifies the user's emotional state. Through computer analysis, emotional nuances are extracted from the text data, detecting emotions such as anxiety, joy, and anticipation. The emotional information becomes the output of this step.

[0363] Step 6:

[0364] The server generates feedback that takes emotional information into account. For example, if the user is feeling anxious, it will generate encouraging messages or positive information from past success stories. The generated feedback is then displayed in the user interface as the final output.

[0365] Step 7:

[0366] The device monitors responses to user feedback and adjusts the content of subsequent feedback as needed. By repeating the feedback cycle until the user is satisfied, it is possible to address user concerns and questions.

[0367] (Application Example 2)

[0368] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0369] Traditional knowledge management systems often fail to address user concerns and questions because they merely provide historical data without considering user emotions. Furthermore, especially in e-commerce, understanding customer emotions and providing appropriate information and support is crucial for improving the customer experience. However, this process is not currently well-implemented, creating a need for a system capable of flexible and effective responses tailored to user emotions.

[0370] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0371] In this invention, the server includes emotion recognition means for analyzing the user's emotions, information presentation means for supporting the project based on the recognized emotions, and information retrieval means for searching a data storage device and obtaining similar work information. This makes it possible to provide past work information based on data entered by the user, while also providing appropriate information and support according to the user's emotional state.

[0372] "User input" refers to the information and data that a user provides to the system.

[0373] "Information input means" refers to devices or programs that have the function of receiving data from users.

[0374] "Information analysis means" refers to devices or programs used to process and analyze received data.

[0375] An "information retrieval means" is a device or program that has the function of searching a data storage device and retrieving related information.

[0376] "Information provision means" refers to devices or programs that have the function of presenting analyzed and retrieved information to the user.

[0377] "Information and communication means" refers to devices and programs used to send and receive data between users and other parties.

[0378] A "data update means" is a device or program that has the function of updating the contents of a data storage device based on new information or user evaluations.

[0379] "Emotion recognition means" refers to devices or programs used to analyze and recognize a user's emotions.

[0380] An "information presentation means" is a device or program that has the function of showing the user appropriate support information in accordance with the results of the emotion recognition means.

[0381] "Data generation means" refers to devices or programs that have the function of organizing and structuring past work information and providing it in a new format.

[0382] This invention comprises a system that effectively supports project progress by analyzing user input and emotional states. The system recognizes emotions from text and voice input by the user via a terminal such as a smartphone or personal computer, and provides appropriate information based on that.

[0383] The terminal receives input information from the user and sends it to the server. The server incorporates information analysis, information retrieval, and emotion recognition capabilities. The information analysis capabilities analyze the input information to identify the characteristics and objectives of the project. The information retrieval capabilities search and retrieve information on similar past projects from the data storage device. Finally, the emotion recognition capabilities use an AI model to determine the user's emotions from the input data.

[0384] For example, when a user inputs project information related to new product development, and their emotions such as tension and anxiety are analyzed, the system presents the user with information on past success stories and encouraging messages. Then, using appropriate information presentation methods, it provides the user with practical advice and strategies based on the analyzed data. This is expected to improve user motivation and reduce anxiety.

[0385] As a concrete example, when a customer purchases a product on an online shop and writes a review, we can consider a prompt that automatically analyzes their emotions and provides information to improve their satisfaction. An example of such a prompt would be, "Analyze the user's emotions from this review and provide appropriate advice." In this way, the system can improve the customer experience and provide better service.

[0386] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0387] Step 1:

[0388] The terminal receives project information from the user as text or voice data. The input data is formatted by the terminal and sent to the server. At this stage, the data entered by the user is collected in its raw state.

[0389] Step 2:

[0390] The server analyzes the received data using information analysis tools. Specifically, it tokenizes text data using natural language processing techniques and extracts project characteristics and objectives. It identifies keywords and context from the input data and prepares it for searching for similar projects in a database. The analyzed information is then supplied to the search tools.

[0391] Step 3:

[0392] The server's information retrieval mechanism searches data storage devices and retrieves information on similar projects. It indexes records within the database and extracts data based on criteria that match the analysis results. The search results include past project success stories and strategies. This information is then passed to the information provision mechanism.

[0393] Step 4:

[0394] The server's emotion recognition system uses a generative AI model to recognize the user's emotions from received text or audio data. It analyzes the emotional nuances of the input data and determines emotional states such as positive, negative, or neutral. The recognized emotion information is then sent to the information presentation system within the server.

[0395] Step 5:

[0396] The server's information presentation method constructs support information for the user based on acquired similar project information and sentiment recognition results. For example, it combines advice based on past success stories with messages to alleviate emotions. This content is sent to the terminal and displayed to the user.

[0397] Step 6:

[0398] User reactions and feedback are sent back to the server via the device. This feedback is recorded and updated in the database by a data update mechanism, and reflected in future system improvements and accuracy enhancements. In this way, the system is continuously improved, enabling the provision of more personalized user support.

[0399] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0400] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0401] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0402] [Third Embodiment]

[0403] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0404] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0405] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0406] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0407] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0408] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0409] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0410] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0411] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0412] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0413] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0414] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0415] This invention provides a knowledge management system that supports the efficient execution of new projects in large corporations. The system is designed to allow users to input project-related information, thereby effectively leveraging insights gained from similar past projects.

[0416] Specifically, when a user enters project details using their device, that data is sent to the server. The server searches its database based on the received information and extracts similar project examples. In this process, generative AI is used to perform advanced pattern recognition and efficiently find relevant data based on the characteristics of the project.

[0417] The server then organizes the acquired data and formats it for user presentation. The terminal displays this data, providing the user with insights including relevant outputs such as presentation materials and Excel files. Furthermore, the user can access an interface through the terminal that allows them to contact past project stakeholders. This enables them to directly obtain specific advice and experience-based insights.

[0418] Furthermore, user feedback is sent to the server via the device, and the server updates its database based on this feedback, ensuring that the information is always up-to-date. This process makes it possible to provide more accurate information for similar projects in the future.

[0419] As a concrete example, imagine a user planning a marketing project for a new product accessing the system and entering project information. In this case, the server identifies marketing strategies for similar products that have been successful in the past and provides relevant materials and data. This allows the user to explore approaches to optimize their own project while referring to past success stories.

[0420] Thus, the system of the present invention can support the launch of new projects and increase their success rate, even in the complex organizational structures of large corporations.

[0421] The following describes the processing flow.

[0422] Step 1:

[0423] The user uses their device to enter information about the new project. This includes a project overview, the industry involved, and the target deliverables.

[0424] Step 2:

[0425] The terminal sends information entered by the user to the server. The data is appropriately formatted and may be sent in JSON format or other formats.

[0426] Step 3:

[0427] The server analyzes the received project information and prepares to search the database based on that information. This analysis includes extracting topics and keywords from the information.

[0428] Step 4:

[0429] The server searches the database for similar past projects. This search uses generative AI and pattern matching algorithms to identify cases that most closely resemble the project's characteristics.

[0430] Step 5:

[0431] The server extracts relevant knowledge and output from the search results and selects the information to provide to the user. This includes related documents and files (presentation materials, data sheets, etc.).

[0432] Step 6:

[0433] The server formats the selected information into a user-friendly format and sends it to the terminal. The terminal then displays this information in its user interface.

[0434] Step 7:

[0435] Users can view information provided through their devices and, if necessary, use an interface to contact members who were involved in past projects. This feature allows them to obtain direct advice and opinions.

[0436] Step 8:

[0437] Users input newly acquired knowledge and work feedback into the server via their terminals. This allows the server to update its knowledge base and store the data as useful for future projects.

[0438] (Example 1)

[0439] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0440] The problem that this invention aims to solve is to provide a system that can effectively collect and utilize information to support the efficient execution of new activities in large corporations. Users have difficulty effectively utilizing the knowledge gained from past activities, and there is a problem that they cannot make appropriate judgments or plans quickly.

[0441] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0442] In this invention, the server includes means for receiving user input, means for performing pattern recognition using a generative AI model and efficiently extracting relevant information, and means for receiving user feedback and updating the database. This enables users to make effective decisions and optimize new activities based on past cases.

[0443] "User input" refers to project-related data and information that users provide to the system.

[0444] A "generative AI model" refers to artificial intelligence technology that recognizes patterns from past project data and extracts relevant information.

[0445] A "database" refers to a collection of information that stores records of various project information and is structured for retrieval.

[0446] "Pattern recognition" refers to a technology that automatically detects commonalities and features hidden within data.

[0447] "Feedback" refers to responses and opinions based on the results and evaluations of a project that a user provides to the system.

[0448] "Formatting" refers to processing acquired information into a format that is easy for users to understand and then displaying it.

[0449] "Communication methods" refer to the methods and technologies that users use to contact past project managers.

[0450] Embodiments of the present invention will now be described. The present invention is a system that supports the efficient execution of new activities in large corporations and is composed of collaboration between users, servers, and terminals.

[0451] The user uses a terminal to enter information related to the new activity. This terminal has an interface designed to reliably accept user input, providing screens for entering specific items such as project name, purpose, budget, and deadline. The entered data is securely transmitted to the server in an encrypted format.

[0452] The server searches the database based on the received information and identifies similar past activity data. In this step, a generative AI model is used, employing advanced pattern recognition to efficiently extract relevant information based on the project's characteristics. Next, the server organizes the acquired data and formats it for user presentation. This information is provided in visual formats such as reports and graphs to ensure user understanding.

[0453] The terminal displays information sent from the server, visually presenting information to the user. This allows the user to obtain concrete guidelines for planning and executing new activities by referring to past examples. The terminal is also equipped with communication methods for contacting past project managers, making it easy to obtain specific feedback and advice via email or chat.

[0454] Furthermore, user feedback is sent to the server via the device, and the server updates the database to reflect this feedback, improving search accuracy for subsequent searches.

[0455] As a concrete example, consider a user developing a marketing strategy for a new product. In this case, the user would enter a prompt such as, "I am currently formulating a market launch strategy for new product B. What can I learn from past success stories?" and the system would then present past success stories. This process would enable the user to form a concrete strategy to optimize their own activities.

[0456] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0457] Step 1:

[0458] The user uses a terminal to enter information related to the new activity. The entered data includes items such as project name, purpose, budget, and deadline. This information entered by the user is collected by the terminal as digital data and sent to the server in an encrypted format.

[0459] Step 2:

[0460] Based on the user input received, the server searches the database for similar past activity information. It utilizes the project information obtained as input to perform advanced pattern recognition using a generative AI model. In this process, the server selects relevant projects from past data and extracts related information based on their characteristics.

[0461] Step 3:

[0462] The server organizes and formats data on similar projects retrieved through searches. It organizes the extracted project information as input and formats it into a visually easy-to-understand format for presentations and reports. This formatted data is then output to the user.

[0463] Step 4:

[0464] The terminal receives formatted information sent from the server and displays it to the user. The terminal uses visual tools, such as graphs and charts, to present the information in a way that the user can intuitively understand. This allows the user to develop concrete plans for current activities based on past examples.

[0465] Step 5:

[0466] Users can contact past project managers via their devices. The devices are equipped with communication tools such as email and chat to ask questions and seek advice from managers. This feature allows users to directly access past experience and expertise.

[0467] Step 6:

[0468] User feedback is sent to the server via the terminal. The server verifies the feedback and adds / updates the newly acquired knowledge to the database. This strengthens the system's overall knowledge base and improves the accuracy of future inquiries.

[0469] (Application Example 1)

[0470] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0471] Regarding the efficient execution of new projects on-site, there is a problem in work environments such as factories where it is difficult to refer to past knowledge and case studies in a timely manner. Furthermore, when hands are full or when it is necessary to advance a project quickly, there is a need for more immediate and effective information gathering and processing. Therefore, the present invention aims to provide a system that allows easy real-time access to past project information and utilizes voice control to enable users to quickly obtain information and support their work.

[0472] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0473] In this invention, the server includes an input means for receiving user input, a visualization means for displaying information in real time, and a control means for enabling operation by voice control. This allows users to quickly access necessary information by voice control while visually checking past project information in real time at a factory or other work site.

[0474] "An input method that accepts user input" refers to an interface that allows users to provide information about new projects to the system.

[0475] "Analysis method" refers to a processing method for structuring received user input and identifying project characteristics.

[0476] "Search method" refers to a function that retrieves past project information from a database and extracts similar cases.

[0477] "Means of provision" refers to the means of displaying the searched information in an easy-to-understand manner for the user.

[0478] "Means of communication" refers to methods for contacting personnel involved in past projects.

[0479] "Update methods" refer to methods for receiving user feedback and keeping the database content constantly up-to-date.

[0480] "Visualization means" refers to display technologies for showing project information to users in real time.

[0481] "Control means" refers to an interface for operating the system using voice or other sensory inputs.

[0482] This invention is a system for efficiently executing new projects on a factory floor. The system is designed to allow users to access project information in real time using smart glasses or other wearable devices.

[0483] The server analyzes data received through user input and searches for similar project information in the database. During this process, it uses a generative AI model to perform advanced pattern recognition and extract past cases related to the project.

[0484] The acquired information is displayed on the user's terminal using visualization tools. This allows the user to visually confirm project-specific information. Voice control is also provided, enabling users to easily access and operate the system using voice commands.

[0485] For example, when a factory worker introducing a new painting technique inputs project information, the server can extract data from similar past projects and provide information such as successful paint formulations and temperature settings. This allows the worker to quickly acquire the necessary knowledge and optimize the project.

[0486] An example of a prompt for the generated AI model is: "Search for past project data related to the new painting process. Display related documents in Japanese."

[0487] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0488] Step 1:

[0489] The user inputs information about a new project through smart glasses. This input may include the project name, related keywords, or voice commands. Upon receiving this input, the system obtains the data necessary for the next process.

[0490] Step 2:

[0491] The terminal sends the received input information to the server. The server analyzes the data and structures it to identify project characteristics. In this process, it extracts necessary data attributes and converts the format.

[0492] Step 3:

[0493] The server performs a database search using the analyzed data. By utilizing a generative AI model and performing advanced pattern recognition, it extracts information on similar past projects. This search yields a dataset of related projects.

[0494] Step 4:

[0495] The server displays the extracted information on the user's terminal in real time using visualization tools. The displayed data includes a list of materials used, process steps, and past success stories. At this point, the data is formatted for the user to visually review.

[0496] Step 5:

[0497] Users interact with the displayed information using voice control. Voice commands allow them to navigate to specific data and view details. This enables users to quickly access the information they need and use it to carry out their projects.

[0498] Step 6:

[0499] When a user provides feedback, the device sends it to the server. The server reflects this in the database and updates the information. This update ensures that more accurate data is provided the next time information is searched for in the project.

[0500] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0501] This invention combines a system for efficiently managing knowledge in new projects for large corporations with an emotion engine that recognizes user emotions. The system aims to improve project success rates by not only providing insights from similar past projects based on user input, but also analyzing user emotions through the emotion engine to provide more appropriate support.

[0502] Specifically, first, the user inputs information related to the new project through a terminal. This information is sent to the server, where the project's characteristics and objectives are identified through analysis. The server then searches the database to retrieve information on similar projects. This information is then provided to the user through the user interface.

[0503] Furthermore, the emotion engine analyzes user input (text and voice) to recognize emotions. This emotional information is used to adjust the user interface and provide feedback to the user. For example, if the system detects that a user is feeling anxious about a project, it is designed to boost the user's motivation by presenting past project success stories and encouraging messages.

[0504] As a concrete example, consider a scenario where a user uses this system when launching a new product development project. In this case, the user inputs an overview of the project into a terminal, and simultaneously, the emotion engine recognizes the user's anxieties. This system not only introduces past success stories that are helpful for project progress, but also presents the specific strategies and countermeasures used in those cases. Furthermore, positive feedback and advice from those who were responsible for the successful projects are also provided.

[0505] Through these means, the present invention supports the execution process of prospective projects and contributes to reducing user anxiety and stress. As a result, it becomes possible to efficiently execute new projects and increase the success rate even within the complex organizational structure of large corporations.

[0506] The following describes the processing flow.

[0507] Step 1:

[0508] Users use their devices to enter detailed information about a new project. This information includes the project's objectives, target market, and desired outcomes. In addition, comments and opinions from the user may also be entered.

[0509] Step 2:

[0510] The terminal sends the entered information to the server. The transmitted data is structured, and each attribute of the project is appropriately tagged.

[0511] Step 3:

[0512] The server receives the project information and extracts the project's key characteristics using analysis tools. Furthermore, it searches the database based on this information to identify similar past projects.

[0513] Step 4:

[0514] The server organizes data on similar projects extracted from search results. It generates an information set to provide to the user, including relevant documents, deliverables, and success factors.

[0515] Step 5:

[0516] Based on the information entered by the user, the emotion engine analyzes the user's text and voice information to recognize their current emotional state. For example, it may determine that the user is feeling stressed.

[0517] Step 6:

[0518] Based on the analysis results of the emotion engine, the server dynamically adjusts the feedback and advice given to the user. This may include encouraging messages based on success stories and practical advice for stress reduction.

[0519] Step 7:

[0520] The terminal displays information and feedback received from the server in its user interface. Users can view this information and, if necessary, select actions by following the on-screen instructions.

[0521] Step 8:

[0522] Users input insights gained and feedback on project progress into the server via their terminals. The server uses this feedback to update its database and improve the accuracy of future project support.

[0523] (Example 2)

[0524] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0525] In new projects at large corporations, the challenge lies in efficiently leveraging knowledge from past projects and providing support that takes user emotions into consideration, thereby improving the project's success rate. In particular, there is a need to alleviate user anxiety and stress, and to provide accurate information and emotional support.

[0526] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0527] In this invention, the server includes means for receiving information via a user interface, means for analyzing the received information and identifying emotional information, and means for searching for and retrieving the characteristics of similar projects in data storage. This makes it possible to effectively utilize past knowledge related to the project and provide feedback that responds to the user's emotions.

[0528] A "user interface" is an interface through which a user can input information into a system and receive output.

[0529] A "means for receiving information" refers to a means that receives data entered by a user and passes it to a server for processing.

[0530] "Analysis techniques" are technologies used to process received information and extract meaningful information and emotions from data.

[0531] A "means for identifying emotional information" refers to a means that has the function of analyzing and identifying a user's emotional state based on their input.

[0532] "Data storage" refers to a storage device used to store project information and user input data.

[0533] "Methods for searching and obtaining characteristics of similar projects" refers to methods of searching through past projects for those with similar characteristics to the current project and obtaining that information.

[0534] "Means for generating and providing feedback" refers to a method that has the function of creating and presenting responses in a way that is easy for users to understand, based on the data that has been acquired.

[0535] A "means for adjusting feedback" refers to a function that modifies the content and method of feedback according to the user's emotional state and reaction.

[0536] "Means of providing successful strategies" refers to methods for presenting users with effective strategies and methods used in past projects.

[0537] The system of this invention integrates knowledge sharing and sentiment analysis in project management. Users input project-related information using a terminal. The input information is received by a server, which uses analysis means to identify the characteristics of the project and detects the user's emotions using a sentiment analysis engine.

[0538] The server searches the data storage based on the analyzed information to retrieve information on similar past projects. A specific algorithm is used to retrieve this information, selecting projects with high similarity. For example, if the project objectives and required resources are similar, that example will be selected.

[0539] The acquired project information is restructured in a format tailored to the user's needs by a feedback generation system and displayed on the user interface via the terminal. Feedback based on sentiment analysis is also provided, and if the user is feeling anxious, success stories and encouraging messages are presented. This allows users to receive appropriate support and gain knowledge useful for their own projects.

[0540] As a concrete example, consider a scenario where a user uses this system to launch a development plan for a new product. In this case, the user inputs the project overview, goals, market research results, etc., into the terminal. The system analyzes this information and provides guidance to help the project progress based on similar successful cases from the past. Furthermore, if the emotion engine detects the user's anxiety, it provides encouragement and specific advice.

[0541] An example of a prompt to input to a generative AI model would be, "Please provide examples of similar cases and emotional support in a new product development project." This would allow the system to integrate relevant information and provide comprehensive support to the user.

[0542] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0543] Step 1:

[0544] The user uses a terminal to enter the necessary information for a new project. This information includes the project's purpose, goals, required resources, and planned start date. The entered data is sent to the server in a structured format.

[0545] Step 2:

[0546] The server passes the received information to the analysis tool to identify the project's characteristics and objectives. Specifically, it uses natural language processing techniques to extract keywords and themes from the text data and identify the project's category. The structured data obtained through the analysis becomes the input for the next step.

[0547] Step 3:

[0548] The server searches the data storage based on the analysis results to retrieve similar past project information. A specific algorithm is used for the search, selecting examples that match the project's objectives and conditions. The retrieved project information becomes the output of this step.

[0549] Step 4:

[0550] The terminal displays information retrieved from the server in a user interface. This information includes summaries of similar projects, strategies used, and factors contributing to their success. Users can use this information to consider strategies that may be useful for their own projects.

[0551] Step 5:

[0552] The text entered by the user is then sent to an emotion analysis engine, which identifies the user's emotional state. Through computer analysis, emotional nuances are extracted from the text data, detecting emotions such as anxiety, joy, and anticipation. The emotional information becomes the output of this step.

[0553] Step 6:

[0554] The server generates feedback that takes emotional information into account. For example, if the user is feeling anxious, it will generate encouraging messages or positive information from past success stories. The generated feedback is then displayed in the user interface as the final output.

[0555] Step 7:

[0556] The device monitors responses to user feedback and adjusts the content of subsequent feedback as needed. By repeating the feedback cycle until the user is satisfied, it is possible to address user concerns and questions.

[0557] (Application Example 2)

[0558] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0559] Traditional knowledge management systems often fail to address user concerns and questions because they merely provide historical data without considering user emotions. Furthermore, especially in e-commerce, understanding customer emotions and providing appropriate information and support is crucial for improving the customer experience. However, this process is not currently well-implemented, creating a need for a system capable of flexible and effective responses tailored to user emotions.

[0560] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0561] In this invention, the server includes emotion recognition means for analyzing the user's emotions, information presentation means for supporting the project based on the recognized emotions, and information retrieval means for searching a data storage device and obtaining similar work information. This makes it possible to provide past work information based on data entered by the user, while also providing appropriate information and support according to the user's emotional state.

[0562] "User input" refers to the information and data that a user provides to the system.

[0563] "Information input means" refers to devices or programs that have the function of receiving data from users.

[0564] "Information analysis means" refers to devices or programs used to process and analyze received data.

[0565] An "information retrieval means" is a device or program that has the function of searching a data storage device and retrieving related information.

[0566] "Information provision means" refers to devices or programs that have the function of presenting analyzed and retrieved information to the user.

[0567] "Information and communication means" refers to devices and programs used to send and receive data between users and other parties.

[0568] A "data update means" is a device or program that has the function of updating the contents of a data storage device based on new information or user evaluations.

[0569] "Emotion recognition means" refers to devices or programs used to analyze and recognize a user's emotions.

[0570] An "information presentation means" is a device or program that has the function of showing the user appropriate support information in accordance with the results of the emotion recognition means.

[0571] "Data generation means" refers to devices or programs that have the function of organizing and structuring past work information and providing it in a new format.

[0572] This invention comprises a system that effectively supports project progress by analyzing user input and emotional states. The system recognizes emotions from text and voice input by the user via a terminal such as a smartphone or personal computer, and provides appropriate information based on that.

[0573] The terminal receives input information from the user and sends it to the server. The server incorporates information analysis, information retrieval, and emotion recognition capabilities. The information analysis capabilities analyze the input information to identify the characteristics and objectives of the project. The information retrieval capabilities search and retrieve information on similar past projects from the data storage device. Finally, the emotion recognition capabilities use an AI model to determine the user's emotions from the input data.

[0574] For example, when a user inputs project information related to new product development, and their emotions such as tension and anxiety are analyzed, the system presents the user with information on past success stories and encouraging messages. Then, using appropriate information presentation methods, it provides the user with practical advice and strategies based on the analyzed data. This is expected to improve user motivation and reduce anxiety.

[0575] As a concrete example, when a customer purchases a product on an online shop and writes a review, we can consider a prompt that automatically analyzes their emotions and provides information to improve their satisfaction. An example of such a prompt would be, "Analyze the user's emotions from this review and provide appropriate advice." In this way, the system can improve the customer experience and provide better service.

[0576] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0577] Step 1:

[0578] The terminal receives project information from the user as text or voice data. The input data is formatted by the terminal and sent to the server. At this stage, the data entered by the user is collected in its raw state.

[0579] Step 2:

[0580] The server analyzes the received data using information analysis tools. Specifically, it tokenizes text data using natural language processing techniques and extracts project characteristics and objectives. It identifies keywords and context from the input data and prepares it for searching for similar projects in a database. The analyzed information is then supplied to the search tools.

[0581] Step 3:

[0582] The server's information retrieval mechanism searches data storage devices and retrieves information on similar projects. It indexes records within the database and extracts data based on criteria that match the analysis results. The search results include past project success stories and strategies. This information is then passed to the information provision mechanism.

[0583] Step 4:

[0584] The server's emotion recognition system uses a generative AI model to recognize the user's emotions from received text or audio data. It analyzes the emotional nuances of the input data and determines emotional states such as positive, negative, or neutral. The recognized emotion information is then sent to the information presentation system within the server.

[0585] Step 5:

[0586] The server's information presentation method constructs support information for the user based on acquired similar project information and sentiment recognition results. For example, it combines advice based on past success stories with messages to alleviate emotions. This content is sent to the terminal and displayed to the user.

[0587] Step 6:

[0588] User reactions and feedback are sent back to the server via the device. This feedback is recorded and updated in the database by a data update mechanism, and reflected in future system improvements and accuracy enhancements. In this way, the system is continuously improved, enabling the provision of more personalized user support.

[0589] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0590] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0591] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0592] [Fourth Embodiment]

[0593] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0594] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0595] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0596] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0597] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0598] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0599] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0600] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0601] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0602] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0603] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0604] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0605] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0606] This invention provides a knowledge management system that supports the efficient execution of new projects in large corporations. The system is designed to allow users to input project-related information, thereby effectively leveraging insights gained from similar past projects.

[0607] Specifically, when a user enters project details using their device, that data is sent to the server. The server searches its database based on the received information and extracts similar project examples. In this process, generative AI is used to perform advanced pattern recognition and efficiently find relevant data based on the characteristics of the project.

[0608] The server then organizes the acquired data and formats it for user presentation. The terminal displays this data, providing the user with insights including relevant outputs such as presentation materials and Excel files. Furthermore, the user can access an interface through the terminal that allows them to contact past project stakeholders. This enables them to directly obtain specific advice and experience-based insights.

[0609] Furthermore, user feedback is sent to the server via the device, and the server updates its database based on this feedback, ensuring that the information is always up-to-date. This process makes it possible to provide more accurate information for similar projects in the future.

[0610] As a concrete example, imagine a user planning a marketing project for a new product accessing the system and entering project information. In this case, the server identifies marketing strategies for similar products that have been successful in the past and provides relevant materials and data. This allows the user to explore approaches to optimize their own project while referring to past success stories.

[0611] Thus, the system of the present invention can support the launch of new projects and increase their success rate, even in the complex organizational structures of large corporations.

[0612] The following describes the processing flow.

[0613] Step 1:

[0614] The user uses their device to enter information about the new project. This includes a project overview, the industry involved, and the target deliverables.

[0615] Step 2:

[0616] The terminal sends information entered by the user to the server. The data is appropriately formatted and may be sent in JSON format or other formats.

[0617] Step 3:

[0618] The server analyzes the received project information and prepares to search the database based on that information. This analysis includes extracting topics and keywords from the information.

[0619] Step 4:

[0620] The server searches the database for similar past projects. This search uses generative AI and pattern matching algorithms to identify cases that most closely resemble the project's characteristics.

[0621] Step 5:

[0622] The server extracts relevant knowledge and output from the search results and selects the information to provide to the user. This includes related documents and files (presentation materials, data sheets, etc.).

[0623] Step 6:

[0624] The server formats the selected information into a user-friendly format and sends it to the terminal. The terminal then displays this information in its user interface.

[0625] Step 7:

[0626] Users can view information provided through their devices and, if necessary, use an interface to contact members who were involved in past projects. This feature allows them to obtain direct advice and opinions.

[0627] Step 8:

[0628] Users input newly acquired knowledge and work feedback into the server via their terminals. This allows the server to update its knowledge base and store the data as useful for future projects.

[0629] (Example 1)

[0630] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0631] The problem that this invention aims to solve is to provide a system that can effectively collect and utilize information to support the efficient execution of new activities in large corporations. Users have difficulty effectively utilizing the knowledge gained from past activities, and there is a problem that they cannot make appropriate judgments or plans quickly.

[0632] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0633] In this invention, the server includes means for receiving user input, means for performing pattern recognition using a generative AI model and efficiently extracting relevant information, and means for receiving user feedback and updating the database. This enables users to make effective decisions and optimize new activities based on past cases.

[0634] "User input" refers to project-related data and information that users provide to the system.

[0635] A "generative AI model" refers to artificial intelligence technology that recognizes patterns from past project data and extracts relevant information.

[0636] A "database" refers to a collection of information that stores records of various project information and is structured for retrieval.

[0637] "Pattern recognition" refers to a technology that automatically detects commonalities and features hidden within data.

[0638] "Feedback" refers to responses and opinions based on the results and evaluations of a project that a user provides to the system.

[0639] "Formatting" refers to processing acquired information into a format that is easy for users to understand and then displaying it.

[0640] "Communication methods" refer to the methods and technologies that users use to contact past project managers.

[0641] Embodiments of the present invention will now be described. The present invention is a system that supports the efficient execution of new activities in large corporations and is composed of collaboration between users, servers, and terminals.

[0642] The user uses a terminal to enter information related to the new activity. This terminal has an interface designed to reliably accept user input, providing screens for entering specific items such as project name, purpose, budget, and deadline. The entered data is securely transmitted to the server in an encrypted format.

[0643] The server searches the database based on the received information and identifies similar past activity data. In this step, a generative AI model is used, employing advanced pattern recognition to efficiently extract relevant information based on the project's characteristics. Next, the server organizes the acquired data and formats it for user presentation. This information is provided in visual formats such as reports and graphs to ensure user understanding.

[0644] The terminal displays information sent from the server, visually presenting information to the user. This allows the user to obtain concrete guidelines for planning and executing new activities by referring to past examples. The terminal is also equipped with communication methods for contacting past project managers, making it easy to obtain specific feedback and advice via email or chat.

[0645] Furthermore, user feedback is sent to the server via the device, and the server updates the database to reflect this feedback, improving search accuracy for subsequent searches.

[0646] As a concrete example, consider a user developing a marketing strategy for a new product. In this case, the user would input a prompt such as, "I am currently formulating a market launch strategy for new product B. What can I learn from past success stories?" and the system would then present past success stories. This process would enable the user to form a concrete strategy to optimize their own activities.

[0647] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0648] Step 1:

[0649] The user uses a terminal to enter information related to the new activity. The entered data includes items such as project name, purpose, budget, and deadline. This information entered by the user is collected by the terminal as digital data and sent to the server in an encrypted format.

[0650] Step 2:

[0651] Based on the user input received, the server searches the database for similar past activity information. It utilizes the project information obtained as input to perform advanced pattern recognition using a generative AI model. In this process, the server selects relevant projects from past data and extracts related information based on their characteristics.

[0652] Step 3:

[0653] The server organizes and formats data on similar projects retrieved through searches. It organizes the extracted project information as input and formats it into a visually easy-to-understand format for presentations and reports. This formatted data is then output to the user.

[0654] Step 4:

[0655] The terminal receives formatted information sent from the server and displays it to the user. The terminal uses visual tools, such as graphs and charts, to present the information in a way that the user can intuitively understand. This allows the user to develop concrete plans for current activities based on past examples.

[0656] Step 5:

[0657] Users can contact past project managers via their devices. The devices are equipped with communication tools such as email and chat to ask questions and seek advice from managers. This feature allows users to directly access past experience and expertise.

[0658] Step 6:

[0659] User feedback is sent to the server via the terminal. The server verifies the feedback and adds / updates the newly acquired knowledge to the database. This strengthens the system's overall knowledge base and improves the accuracy of future inquiries.

[0660] (Application Example 1)

[0661] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0662] Regarding the efficient execution of new projects on-site, there is a problem in work environments such as factories where it is difficult to refer to past knowledge and case studies in a timely manner. Furthermore, when hands are full or when it is necessary to advance a project quickly, there is a need for more immediate and effective information gathering and processing. Therefore, the present invention aims to provide a system that allows easy real-time access to past project information and utilizes voice control to enable users to quickly obtain information and support their work.

[0663] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0664] In this invention, the server includes an input means for receiving user input, a visualization means for displaying information in real time, and a control means for enabling operation by voice control. This allows users to quickly access necessary information by voice control while visually checking past project information in real time at a factory or other work site.

[0665] "An input method that accepts user input" refers to an interface that allows users to provide information about new projects to the system.

[0666] "Analysis method" refers to a processing method for structuring received user input and identifying project characteristics.

[0667] "Search method" refers to a function that retrieves past project information from a database and extracts similar cases.

[0668] "Means of provision" refers to the means of displaying the searched information in an easy-to-understand manner for the user.

[0669] "Means of communication" refers to methods for contacting personnel involved in past projects.

[0670] "Update methods" refer to methods for receiving user feedback and keeping the database content constantly up-to-date.

[0671] "Visualization means" refers to display technologies for showing project information to users in real time.

[0672] "Control means" refers to an interface for operating the system using voice or other sensory inputs.

[0673] This invention is a system for efficiently executing new projects on a factory floor. The system is designed to allow users to access project information in real time using smart glasses or other wearable devices.

[0674] The server analyzes data received through user input and searches for similar project information in the database. During this process, it uses a generative AI model to perform advanced pattern recognition and extract past cases related to the project.

[0675] The acquired information is displayed on the user's terminal using visualization tools. This allows the user to visually confirm project-specific information. Voice control is also provided, enabling users to easily access and operate the system using voice commands.

[0676] For example, when a factory worker introducing a new painting technique inputs project information, the server can extract data from similar past projects and provide information such as successful paint formulations and temperature settings. This allows the worker to quickly acquire the necessary knowledge and optimize the project.

[0677] An example of a prompt for the generated AI model is: "Search for past project data related to the new painting process. Display related documents in Japanese."

[0678] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0679] Step 1:

[0680] The user inputs information about a new project through smart glasses. This input may include the project name, related keywords, or voice commands. Upon receiving this input, the system obtains the data necessary for the next process.

[0681] Step 2:

[0682] The terminal sends the received input information to the server. The server analyzes the data and structures it to identify project characteristics. In this process, it extracts necessary data attributes and converts the format.

[0683] Step 3:

[0684] The server performs a database search using the analyzed data. By utilizing a generative AI model and performing advanced pattern recognition, it extracts information on similar past projects. This search yields a dataset of related projects.

[0685] Step 4:

[0686] The server displays the extracted information on the user's terminal in real time using visualization tools. The displayed data includes a list of materials used, process steps, and past success stories. At this point, the data is formatted for the user to visually review.

[0687] Step 5:

[0688] Users interact with the displayed information using voice control. Voice commands allow them to navigate to specific data and view details. This enables users to quickly access the information they need and use it to carry out their projects.

[0689] Step 6:

[0690] When a user provides feedback, the device sends it to the server. The server reflects this in the database and updates the information. This update ensures that more accurate data is provided the next time information is searched for in the project.

[0691] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0692] This invention combines a system for efficiently managing knowledge in new projects for large corporations with an emotion engine that recognizes user emotions. The system aims to improve project success rates by not only providing insights from similar past projects based on user input, but also analyzing user emotions through the emotion engine to provide more appropriate support.

[0693] Specifically, first, the user inputs information related to the new project through a terminal. This information is sent to the server, where the project's characteristics and objectives are identified through analysis. The server then searches the database to retrieve information on similar projects. This information is then provided to the user through the user interface.

[0694] Furthermore, the emotion engine analyzes user input (text and voice) to recognize emotions. This emotional information is used to adjust the user interface and provide feedback to the user. For example, if the system detects that a user is feeling anxious about a project, it is designed to boost the user's motivation by presenting past project success stories and encouraging messages.

[0695] As a concrete example, consider a scenario where a user uses this system when launching a new product development project. In this case, the user inputs an overview of the project into a terminal, and simultaneously, the emotion engine recognizes the user's anxieties. This system not only introduces past success stories that are helpful for project progress, but also presents the specific strategies and countermeasures used in those cases. Furthermore, positive feedback and advice from those who were responsible for the successful projects are also provided.

[0696] Through these means, the present invention supports the execution process of prospective projects and contributes to reducing user anxiety and stress. As a result, it becomes possible to efficiently execute new projects and increase the success rate even within the complex organizational structure of large corporations.

[0697] The following describes the processing flow.

[0698] Step 1:

[0699] Users use their devices to enter detailed information about a new project. This information includes the project's objectives, target market, and desired outcomes. In addition, comments and opinions from the user may also be entered.

[0700] Step 2:

[0701] The terminal sends the entered information to the server. The transmitted data is structured, and each attribute of the project is appropriately tagged.

[0702] Step 3:

[0703] The server receives the project information and extracts the project's key characteristics using analysis tools. Furthermore, it searches the database based on this information to identify similar past projects.

[0704] Step 4:

[0705] The server organizes data on similar projects extracted from search results. It generates an information set to provide to the user, including relevant documents, deliverables, and success factors.

[0706] Step 5:

[0707] Based on the information entered by the user, the emotion engine analyzes the user's text and voice information to recognize their current emotional state. For example, it may determine that the user is feeling stressed.

[0708] Step 6:

[0709] Based on the analysis results of the emotion engine, the server dynamically adjusts the feedback and advice given to the user. This may include encouraging messages based on success stories and practical advice for stress reduction.

[0710] Step 7:

[0711] The terminal displays information and feedback received from the server in its user interface. Users can view this information and, if necessary, select actions by following the on-screen instructions.

[0712] Step 8:

[0713] Users input insights gained and feedback on project progress into the server via their terminals. The server uses this feedback to update its database and improve the accuracy of future project support.

[0714] (Example 2)

[0715] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0716] In new projects at large corporations, the challenge lies in efficiently leveraging knowledge from past projects and providing support that takes user emotions into consideration, thereby improving the project's success rate. In particular, there is a need to alleviate user anxiety and stress, and to provide accurate information and emotional support.

[0717] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0718] In this invention, the server includes means for receiving information via a user interface, means for analyzing the received information and identifying emotional information, and means for searching for and retrieving the characteristics of similar projects in data storage. This makes it possible to effectively utilize past knowledge related to the project and provide feedback that responds to the user's emotions.

[0719] A "user interface" is an interface through which a user can input information into a system and receive output.

[0720] A "means for receiving information" refers to a means that receives data entered by a user and passes it to a server for processing.

[0721] "Analysis techniques" are technologies used to process received information and extract meaningful information and emotions from data.

[0722] A "means for identifying emotional information" refers to a means that has the function of analyzing and identifying a user's emotional state based on their input.

[0723] "Data storage" refers to a storage device used to store project information and user input data.

[0724] "Methods for searching and obtaining characteristics of similar projects" refers to methods of searching through past projects for those with similar characteristics to the current project and obtaining that information.

[0725] "Means for generating and providing feedback" refers to a method that has the function of creating and presenting responses in a way that is easy for users to understand, based on the data that has been acquired.

[0726] A "means for adjusting feedback" refers to a function that modifies the content and method of feedback according to the user's emotional state and reaction.

[0727] "Means of providing successful strategies" refers to methods for presenting users with effective strategies and methods used in past projects.

[0728] The system of this invention integrates knowledge sharing and sentiment analysis in project management. Users input project-related information using a terminal. The input information is received by a server, which uses analysis means to identify the characteristics of the project and detects the user's emotions using a sentiment analysis engine.

[0729] The server searches the data storage based on the analyzed information to retrieve information on similar past projects. A specific algorithm is used to retrieve this information, selecting projects with high similarity. For example, if the project objectives and required resources are similar, that example will be selected.

[0730] The acquired project information is restructured in a format tailored to the user's needs by a feedback generation system and displayed on the user interface via the terminal. Feedback based on sentiment analysis is also provided, and if the user is feeling anxious, success stories and encouraging messages are presented. This allows users to receive appropriate support and gain knowledge useful for their own projects.

[0731] As a concrete example, consider a scenario where a user uses this system to launch a development plan for a new product. In this case, the user inputs the project overview, goals, market research results, etc., into the terminal. The system analyzes this information and provides guidance to help the project progress based on similar successful cases from the past. Furthermore, if the emotion engine detects the user's anxiety, it provides encouragement and specific advice.

[0732] An example of a prompt to input to a generative AI model would be, "Please provide examples of similar cases and emotional support in a new product development project." This would allow the system to integrate relevant information and provide comprehensive support to the user.

[0733] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0734] Step 1:

[0735] The user uses a terminal to enter the necessary information for a new project. This information includes the project's purpose, goals, required resources, and planned start date. The entered data is sent to the server in a structured format.

[0736] Step 2:

[0737] The server passes the received information to the analysis tool to identify the project's characteristics and objectives. Specifically, it uses natural language processing techniques to extract keywords and themes from the text data and identify the project's category. The structured data obtained through the analysis becomes the input for the next step.

[0738] Step 3:

[0739] The server searches the data storage based on the analysis results to retrieve similar past project information. A specific algorithm is used for the search, selecting examples that match the project's objectives and conditions. The retrieved project information becomes the output of this step.

[0740] Step 4:

[0741] The terminal displays information retrieved from the server in a user interface. This information includes summaries of similar projects, strategies used, and factors contributing to their success. Users can use this information to consider strategies that may be useful for their own projects.

[0742] Step 5:

[0743] The text entered by the user is then sent to an emotion analysis engine, which identifies the user's emotional state. Through computer analysis, emotional nuances are extracted from the text data, detecting emotions such as anxiety, joy, and anticipation. The emotional information becomes the output of this step.

[0744] Step 6:

[0745] The server generates feedback that takes emotional information into account. For example, if the user is feeling anxious, it will generate encouraging messages or positive information from past success stories. The generated feedback is then displayed in the user interface as the final output.

[0746] Step 7:

[0747] The device monitors responses to user feedback and adjusts the content of subsequent feedback as needed. By repeating the feedback cycle until the user is satisfied, it is possible to address user concerns and questions.

[0748] (Application Example 2)

[0749] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0750] Traditional knowledge management systems often fail to address user concerns and questions because they merely provide historical data without considering user emotions. Furthermore, especially in e-commerce, understanding customer emotions and providing appropriate information and support is crucial for improving the customer experience. However, this process is not currently well-implemented, creating a need for a system capable of flexible and effective responses tailored to user emotions.

[0751] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0752] In this invention, the server includes emotion recognition means for analyzing the user's emotions, information presentation means for supporting the project based on the recognized emotions, and information retrieval means for searching a data storage device and obtaining similar work information. This makes it possible to provide past work information based on data entered by the user, while also providing appropriate information and support according to the user's emotional state.

[0753] "User input" refers to the information and data that a user provides to the system.

[0754] "Information input means" refers to devices or programs that have the function of receiving data from users.

[0755] "Information analysis means" refers to devices or programs used to process and analyze received data.

[0756] An "information retrieval means" is a device or program that has the function of searching a data storage device and retrieving related information.

[0757] "Information provision means" refers to devices or programs that have the function of presenting analyzed and retrieved information to the user.

[0758] "Information and communication means" refers to devices and programs used to send and receive data between users and other parties.

[0759] A "data update means" is a device or program that has the function of updating the contents of a data storage device based on new information or user evaluations.

[0760] "Emotion recognition means" refers to devices or programs used to analyze and recognize a user's emotions.

[0761] An "information presentation means" is a device or program that has the function of showing the user appropriate support information in accordance with the results of the emotion recognition means.

[0762] "Data generation means" refers to devices or programs that have the function of organizing and structuring past work information and providing it in a new format.

[0763] This invention comprises a system that effectively supports project progress by analyzing user input and emotional states. The system recognizes emotions from text and voice input by the user via a terminal such as a smartphone or personal computer, and provides appropriate information based on that.

[0764] The terminal receives input information from the user and sends it to the server. The server incorporates information analysis, information retrieval, and emotion recognition capabilities. The information analysis capabilities analyze the input information to identify the characteristics and objectives of the project. The information retrieval capabilities search and retrieve information on similar past projects from the data storage device. Finally, the emotion recognition capabilities use an AI model to determine the user's emotions from the input data.

[0765] For example, when a user inputs project information related to new product development, and their emotions such as tension and anxiety are analyzed, the system presents the user with information on past success stories and encouraging messages. Then, using appropriate information presentation methods, it provides the user with practical advice and strategies based on the analyzed data. This is expected to improve user motivation and reduce anxiety.

[0766] As a concrete example, when a customer purchases a product on an online shop and writes a review, we can consider a prompt that automatically analyzes their emotions and provides information to improve their satisfaction. An example of such a prompt would be, "Analyze the user's emotions from this review and provide appropriate advice." In this way, the system can improve the customer experience and provide better service.

[0767] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0768] Step 1:

[0769] The terminal receives project information from the user as text or voice data. The input data is formatted by the terminal and sent to the server. At this stage, the data entered by the user is collected in its raw state.

[0770] Step 2:

[0771] The server analyzes the received data using information analysis tools. Specifically, it tokenizes text data using natural language processing techniques and extracts project characteristics and objectives. It identifies keywords and context from the input data and prepares it for searching for similar projects in a database. The analyzed information is then supplied to the search tools.

[0772] Step 3:

[0773] The server's information retrieval mechanism searches data storage devices and retrieves information on similar projects. It indexes records within the database and extracts data based on criteria that match the analysis results. The search results include past project success stories and strategies. This information is then passed to the information provision mechanism.

[0774] Step 4:

[0775] The server's emotion recognition system uses a generative AI model to recognize the user's emotions from received text or audio data. It analyzes the emotional nuances of the input data and determines emotional states such as positive, negative, or neutral. The recognized emotion information is then sent to the information presentation system within the server.

[0776] Step 5:

[0777] The server's information presentation method constructs support information for the user based on acquired similar project information and sentiment recognition results. For example, it combines advice based on past success stories with messages to alleviate emotions. This content is sent to the terminal and displayed to the user.

[0778] Step 6:

[0779] User reactions and feedback are sent back to the server via the device. This feedback is recorded and updated in the database by a data update mechanism, and reflected in future system improvements and accuracy enhancements. In this way, the system is continuously improved, enabling the provision of more personalized user support.

[0780] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0781] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0782] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0783] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0784] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0785] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0786] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0787] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0788] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0789] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0790] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0791] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0792] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0793] 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.

[0794] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0795] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0796] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0797] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0798] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0799] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0800] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0801] The following is further disclosed regarding the embodiments described above.

[0802] (Claim 1)

[0803] An input means for receiving user input,

[0804] An analysis means for analyzing the information received by the input means,

[0805] A search method that searches a database and retrieves similar project information,

[0806] A means for providing project information obtained by the search means to the user,

[0807] A means of communication to contact the person in charge of past projects,

[0808] A means of updating the database by receiving user feedback,

[0809] ...

[0810] A system that includes this.

[0811] (Claim 2)

[0812] The system according to claim 1, comprising a generation means for organizing and structuring past project information and providing it.

[0813] (Claim 3)

[0814] The system according to claim 1, which has a function to provide guidance for improving the success rate of new projects using the knowledge acquired by the user.

[0815] "Example 1"

[0816] (Claim 1)

[0817] A means of receiving user input,

[0818] A means for searching a database based on the aforementioned input and obtaining similar activity information,

[0819] A method for efficiently extracting relevant information by performing pattern recognition using a generative AI model,

[0820] A means for formatting the acquired information into a format to be provided to the user,

[0821] A means of communication to contact the person in charge via a terminal,

[0822] A means of receiving user feedback and updating the database,

[0823] ...

[0824] A system that includes this.

[0825] (Claim 2)

[0826] The system according to claim 1, comprising a generation means for organizing and structuring past activity information and providing it.

[0827] (Claim 3)

[0828] The system according to claim 1, which has a function to provide guidance to improve the success rate of new activities using the knowledge acquired by the user.

[0829] "Application Example 1"

[0830] (Claim 1)

[0831] An input means for receiving user input,

[0832] An analysis means for analyzing the information received by the input means,

[0833] A search method that searches a database and retrieves similar project information,

[0834] A means for providing project information obtained by the search means to the user,

[0835] A means of communication to contact the person in charge of past projects,

[0836] A means of updating the database by receiving user feedback,

[0837] A visualization method for displaying information in real time,

[0838] A control means that enables operation by voice control,

[0839] A system that includes this.

[0840] (Claim 2)

[0841] The system according to claim 1, comprising a generation means for organizing and structuring past project information and providing it.

[0842] (Claim 3)

[0843] The system according to claim 1, which has a function to provide guidance that improves the success rate of new projects using the knowledge acquired by the user, as well as a function to provide guidance that can be quickly implemented from voice-controlled visualization information.

[0844] "Example 2 of combining an emotion engine"

[0845] (Claim 1)

[0846] A means of receiving information through a user interface,

[0847] A means for analyzing the received information and identifying emotional information,

[0848] A means of searching for and retrieving the characteristics of similar projects within data storage,

[0849] A means for generating and providing feedback based on the information acquired,

[0850] A means of adjusting user feedback based on emotions,

[0851] A means of providing successful strategies derived from past cases,

[0852] A system that includes this.

[0853] (Claim 2)

[0854] The system according to claim 1, which organizes past project information and provides it as structured data.

[0855] (Claim 3)

[0856] The system according to claim 1, which has a function to provide guidance for improving the success rate of new projects using the knowledge acquired by the user and the results of sentiment analysis.

[0857] "Application example 2 when combining with an emotional engine"

[0858] (Claim 1)

[0859] An information input means that accepts user input,

[0860] An information analysis means for analyzing the data received by the information input means,

[0861] An information retrieval means for searching a data storage device and obtaining similar work information,

[0862] Information provision means that provides work information obtained by the information retrieval means to the user,

[0863] Information and communication means to contact relevant parties involved in past work,

[0864] A data update means that receives user feedback and updates the data storage device,

[0865] A means of recognizing emotions to analyze the user's emotions,

[0866] Information presentation methods to support projects based on recognized emotions,

[0867] A system that includes this.

[0868] (Claim 2)

[0869] The system according to claim 1, comprising data generation means for organizing and structuring past work information and providing it.

[0870] (Claim 3)

[0871] The system according to claim 1, which has a function to provide guidance that improves the success rate of new tasks using the knowledge acquired by the user. [Explanation of Symbols]

[0872] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. An input means for receiving user input, An analysis means for analyzing the information received by the input means, A search method that searches a database and retrieves similar project information, A means for providing project information obtained by the search means to the user, A means of communication to contact the person in charge of past projects, A means of updating the database by receiving user feedback, A system that includes this.

2. The system according to claim 1, comprising a generation means for organizing and structuring past project information and providing it.

3. The system according to claim 1, which has a function to provide guidance for improving the success rate of new projects using the knowledge acquired by the user.

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