system

Abstract

We provide the system. [Solution] Means of collecting research information, A means of analyzing collected research information using natural language processing technology, A means of proposing a research process to the user based on the analyzed results, A means of providing learning materials to support the improvement of expertise for new users, A means of notifying expert users of the latest research results and technological trends, A means of recording users' technical knowledge and thought processes, and accumulating knowledge within the organization, 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 and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of the chatbot's 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] In the field of research and development, it is difficult for researchers to quickly acquire specialized knowledge, and this process can be a significant burden, especially for new researchers. In addition, the continuity of projects may be impaired due to the retirement or job transfer of researchers with high expertise. Furthermore, there is a lack of means to efficiently track the latest research trends and technological trends, and information collection is also a burden for experts. To solve such problems, an integrated system that can streamline the research process, support the improvement of expertise, and enable knowledge accumulation is required.

Means for Solving the Problems

[0005] This invention solves the above problems by providing a system that automatically collects research information and analyzes it using natural language processing technology. This system proposes research processes based on user input and supports the improvement of expertise by providing learning materials to newcomers. It also notifies experts of the latest research results and technological trends, enabling efficient information gathering. Furthermore, it records users' technical knowledge and thought processes, accumulating them as knowledge within the organization, thereby providing a means to prevent the loss of skills due to resignation or job changes. This ensures improved researcher productivity and project continuity.

[0006] "Research information" refers to all data and information that researchers need to advance their research, such as papers, articles, and datasets related to science and technology.

[0007] "Natural language processing technology" refers to techniques for understanding, interpreting, and generating human language using computers, and includes methods such as text analysis and speech recognition.

[0008] "Users" refer to researchers who receive research support through this system, primarily both newcomers and experts, who require information and support tailored to their respective needs.

[0009] "Research process suggestions" are guidelines designed to improve researchers' work efficiency by having AI suggest effective research methods and procedures according to the research theme and objectives.

[0010] "Learning materials" are educational resources provided to improve the specialized knowledge of new employees, and include summaries of relevant knowledge and quizzes to aid understanding.

[0011] "Enhancing expertise" refers to researchers improving their knowledge and skills in their field, enabling them to conduct more advanced research.

[0012] "Notification of the latest research results and technological trends" refers to the act of providing expert users with a summary of the latest information in their respective fields, thereby supporting the efficient gathering of information.

[0013] "Recording technical knowledge and thought processes" refers to a means of accumulating knowledge by preserving researchers' specialized knowledge and thought processes in their research, and by sharing and utilizing this information throughout the organization.

[0014] "Knowledge accumulation" refers to the systematic preservation of the knowledge and skills possessed by individual researchers, making them accessible and usable by other researchers, thereby achieving technology sharing and long-term preservation. [Brief explanation of the drawing]

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

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

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

[0018] In the following embodiments, a 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.

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

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

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

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

[0023] [First Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0036] This invention is implemented as a system for streamlining the research and development process using AI. The system consists of a server, a terminal, and a user interface.

[0037] The server connects to online scientific paper databases and technical article websites, automatically collecting necessary research information via APIs. The collected data is analyzed on the server using natural language processing technology to extract important information and trends. This process allows for efficient understanding of the latest research trends.

[0038] The terminal acts as the interface with the user, receiving research topics and questions from the user. Users can input questions or topics related to a specific research field and receive research processes suggested by the server based on that input. The terminal also provides learning materials from the server to new users, supporting their professional development. These learning materials include foundational knowledge in related fields and quiz-style training to help new users deepen their understanding.

[0039] For expert users, the server notifies them of the latest research findings and technological trends analyzed by the server. This allows experts to easily access the latest information. The terminal also records the user's actions and thought processes and sends this data to the server. This data is stored in the organization's database and used for future projects and researcher training.

[0040] As a concrete example, when a junior chemistry researcher (user) is working on synthesizing a new material, they can receive summaries of relevant literature and experimental design suggestions from the server via their terminal. This allows the user to proceed with their research with confidence and improve their expertise in a short period of time. Furthermore, expert users can quickly determine the direction of their research based on information on new synthesis methods and technological trends provided by the server. In this way, the present invention effectively functions as a system that improves the productivity of researchers and contributes to the advancement of technology.

[0041] The following describes the processing flow.

[0042] Step 1:

[0043] The server accesses online scientific paper databases and technical article websites, using APIs to collect relevant research information. The collected information is then filtered based on specific keywords or queries.

[0044] Step 2:

[0045] The server analyzes the research information it collects using natural language processing techniques. Topic modeling and keyword extraction are used to identify important technological trends and developments within the data.

[0046] Step 3:

[0047] The terminal receives research topics and questions from the user. The user inputs specific questions or interests related to their research, and that information is sent to the server.

[0048] Step 4:

[0049] The server uses an AI model to propose a research process based on the user's input. Specifically, it generates recommendations including appropriate experimental design and research flow, and sends them to the terminal.

[0050] Step 5:

[0051] The device displays learning materials for new users based on output from an AI model. These materials include summaries of basic knowledge and assessments in the form of quizzes.

[0052] Step 6:

[0053] The server summarizes the latest research findings and technological trends and notifies expert users of their terminals. This allows experts to easily access the latest information and quickly decide on the direction of their research.

[0054] Step 7:

[0055] The user records their technical insights and thought processes from their research on a device. The device sends this data to a server, where it is stored in the organization's knowledge database.

[0056] (Example 1)

[0057] 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."

[0058] Traditional research and development processes required manually searching and analyzing vast amounts of literature and materials, which was a significant burden in terms of time and effort. Furthermore, for junior researchers lacking specialized knowledge, support systems for rapidly improving their expertise were insufficient, and opportunities to access the latest research results were limited. This hindered the efficiency and accuracy of research, leading to a slower pace of technological innovation.

[0059] 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.

[0060] In this invention, the server includes a device for collecting research data, a device for analyzing the collected research data using natural language processing technology, and a device for extracting important information and trends from the analyzed data using a generative AI model. This enables efficient handling of large amounts of research data, extraction of important information, and proposal of research processes. Furthermore, it is possible to significantly improve research efficiency and the speed of technological innovation by providing educational materials to new researchers, including basic knowledge of related fields and quizzes, and by immediately notifying experts of the latest research results.

[0061] "Research data" refers to a broad collection of knowledge encompassing information and materials gathered for scientific investigation and technological innovation.

[0062] "Natural language processing technology" refers to technologies for recognizing, understanding, and analyzing human language using computers, and includes methods such as text mining and sentiment analysis.

[0063] A "generative AI model" is an algorithm that uses artificial intelligence technology to learn from large amounts of data and generate natural-sounding text, similar to what humans would write.

[0064] "Educational materials" refer to information and content provided to improve users' expertise, including basic knowledge, quizzes, and summaries of related materials.

[0065] "Important information and trends" refer to meaningful insights and data patterns that indicate progress in research and technological trends.

[0066] "Internet information sources" refer to sources of information accessible via the network, such as websites, databases, and online articles and papers.

[0067] "Operation history" refers to a record of actions and inputs made by a user within the system, and is data used for analysis based on that history.

[0068] This invention is a system for streamlining the research and development process, consisting of a server, terminals, and users. The server is responsible for collecting research data and analyzing it using natural language processing techniques and generative AI models. High-performance servers are required as hardware, and the software includes a database management system, natural language processing libraries, and a framework for running generative AI models.

[0069] The server connects to information sources on the internet and automatically retrieves relevant research data via APIs. This data is analyzed using natural language processing techniques to extract important information and trends. Based on these results, the server proposes research methods to the user.

[0070] On the other hand, the terminal functions as an interface between the user and the server, displaying information and suggestions from the server to the user. Users can receive suggestions from the server by entering specific research topics or questions through the terminal. Educational materials designed for users are provided on the terminal to support the development of new users' expertise. These educational materials include quizzes to deepen basic knowledge and understanding of related fields.

[0071] For example, if a junior chemistry researcher enters the prompt message, "I want to know the latest trends in synthesis methods for new materials," the server generates summaries of relevant literature and proposed experimental designs, which are then displayed on the terminal. In this way, the entire system operates in an integrated manner, streamlining the research and development process and promoting the improvement of the user's knowledge.

[0072] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0073] Step 1:

[0074] The server connects to multiple information sources on the internet and collects research data using APIs. Specifically, the server searches for information sources using specified keywords and stores the retrieved data in a database on the server. The input is the specified keywords and search conditions, and the output is the research data retrieved from the information sources.

[0075] Step 2:

[0076] The server analyzes the collected research data using natural language processing techniques. The server extracts important information and trends from the data using text analysis methods. This process utilizes a generative AI model to generate summaries of relevant papers and articles. The input is the collected research data, and the output is the extracted information and summaries.

[0077] Step 3:

[0078] The terminal displays the analysis results provided by the server to the user. The user can input any prompt text through the terminal, and based on that, will receive suitable suggestions from the server. For example, if a prompt text such as "Please tell me the synthesis method for the new material" is entered, the server will provide information based on the analysis results. The input is the prompt text from the user, and the output is suggestions or information based on the analysis results.

[0079] Step 4:

[0080] The device provides users with educational materials to enhance their expertise. The device displays learning content, including foundational knowledge and quizzes tailored to the user's experience and knowledge level. Input is the user's profile and knowledge level, while output is appropriately customized educational material.

[0081] Step 5:

[0082] The server notifies expert users of the latest research findings and technological trends. Expert users receive these notifications at all times via their terminals and can check detailed information as needed. Inputs are the latest analysis results and the user's areas of interest, and outputs are notifications to expert users.

[0083] Step 6:

[0084] The terminal records the user's operation history and thought process, and sends this data to a server. The server analyzes this data and stores it in the organization's database. The input is the user's operation history and reactions, and the output is the analyzed insights and accumulated knowledge data.

[0085] (Application Example 1)

[0086] 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."

[0087] In modern manufacturing, rapidly changing technological information and the frequent introduction of new materials necessitate the optimization of manufacturing processes. However, information acquisition and analysis are often done manually, leading to challenges such as delays in efficient process improvement and decision-making. Furthermore, training new employees is time-consuming and costly, making it difficult to cultivate them into immediately productive members of the workforce. A system is needed to solve these problems and maximize the efficiency of manufacturing processes.

[0088] 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.

[0089] In this invention, the server includes means for collecting research information, means for analyzing the collected research information using natural language processing technology, and means for collecting technical information for improving efficiency in the manufacturing process and optimizing its operation based on that information. This enables the immediate incorporation of the latest technologies into the manufacturing line and rapid and effective process optimization. Furthermore, it is possible to improve the overall technical knowledge of the organization by providing learning materials to support the improvement of expertise for new employees and notifying expert users of the latest research results and technological trends.

[0090] "Research information" refers to knowledge obtained from scientific and technological papers, articles, and databases.

[0091] "Natural language processing technology" is an artificial intelligence technology that analyzes text data and extracts important information.

[0092] A "manufacturing process" is a set of steps and procedures necessary to complete a product.

[0093] "Efficiency optimization" is an optimization process aimed at achieving maximum results while minimizing resources and time.

[0094] "Technical information" refers to the latest knowledge regarding new technologies, methods, and materials.

[0095] "Optimizing operation" means making adjustments to maximize the performance of a system, machine, or process.

[0096] A "new user" refers to a user who has recently joined a particular field or organization.

[0097] "Learning materials that support the improvement of expertise" refer to educational materials provided to help acquire specific skills or specialized knowledge.

[0098] An "expert user" refers to a user who possesses advanced knowledge and experience in a specific field.

[0099] "Latest research findings and technological trends" refer to information that indicates the newest discoveries and directions of development in current science and technology.

[0100] "Accumulating knowledge" means organizing experiences and information and saving them in a way that can be used in the future.

[0101] The server collects research information and performs analysis using natural language processing technology. It accesses databases and technical article sites on the internet via APIs to obtain the latest technical information. The retrieved information is stored in a database, and important information and technological trends are extracted using natural language processing. This allows users to quickly obtain the information necessary to improve the efficiency of their manufacturing processes.

[0102] The terminal functions as an interface with the user. Through the terminal, users can receive research procedures and suggestions for the latest technologies. The terminal also provides learning materials to help new users improve their expertise, supporting their learning through quiz-based training and summaries of relevant literature. Expert users are notified of the latest research results and technological trends analyzed by the server, helping them optimize manufacturing processes efficiently and effectively.

[0103] This system allows users to share technical insights and thought processes, strengthening the knowledge base across the entire organization. This data will be used for future projects and training new employees.

[0104] For example, if a manufacturing plant plans to introduce a new material, the server collects and analyzes relevant technical information and provides the user with optimal manufacturing procedures and improvement suggestions via a terminal. This allows the plant to quickly begin manufacturing using the properties of the new material.

[0105] An example of a prompt to input into a generative AI model is: "Suggest ways to improve the efficiency of a manufacturing line using AI. How will you collect and analyze information on the latest manufacturing technologies and materials?"

[0106] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0107] Step 1:

[0108] The server accesses databases and article sites on the internet via APIs to retrieve the latest research information. The input consists of URLs of the information sources to be collected and query conditions, while the output includes the retrieved text data. This data is then prepared within the server for the following processing.

[0109] Step 2:

[0110] The server performs analysis on the acquired text data using natural language processing techniques. The input is the text data acquired in the previous step, and the output extracts important information and technology trends. Specific operations include text tokenization, keyword extraction, and topic modeling.

[0111] Step 3:

[0112] The server generates technical information for efficiency improvements based on the analysis results and sends it to the terminal. The inputs used are extracted key information and technology trends, while the output includes optimization suggestions and improvement measures. This operation enables the provision of concrete suggestions to the user.

[0113] Step 4:

[0114] The terminal displays suggested technical information and improvement measures so that the user can view them through the interface. The input is technical information sent from the server, and the output is presented as visual information that the user can view on the screen. Based on this, the user obtains guidance for improving the manufacturing process.

[0115] Step 5:

[0116] Users improve their expertise through quizzes and literature summaries using learning materials provided on their devices. Input includes specific learning themes and fields, and output aims to improve the user's knowledge. Specific actions include interactive quizzes and the display of relevant literature summaries.

[0117] Step 6:

[0118] Expert users receive notifications of the latest research findings and technological trends analyzed by the server via their terminals. The input is the latest analysis results, and the output includes information in the form of notifications. This process allows users to quickly obtain the information necessary to improve their manufacturing processes.

[0119] Step 7:

[0120] The server records user actions and thought processes, and stores the obtained data in the organization's database. Inputs include user behavior data and feedback, while outputs include accumulated knowledge data. Through this process, the knowledge base of the entire organization is strengthened.

[0121] 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.

[0122] This invention is implemented in a form that combines a system for streamlining the research and development process with an emotion engine that recognizes user emotions. This system consists of a server, a terminal, and an emotion engine.

[0123] The server accesses scientific databases and technology article sites on the internet, collecting research information via APIs. The server analyzes this information using natural language processing techniques to identify important technology trends. This enables the efficient collection and analysis of information necessary for research.

[0124] The terminal acts as the interface with the user, receiving research topics and questions from the user. Based on information sent from the server and the analysis results from the emotion engine, the terminal proposes an optimized research process for the user. The emotion engine analyzes the user's facial expressions and voice input to determine their emotional state, and uses that data to personalize the user's experience.

[0125] As a concrete example, when a new user uses a terminal to learn about a new experimental technique, the server collects relevant information and proposes an experimental process based on it. At the same time, an emotion engine monitors the user's emotional state and adjusts the content to provide slower, more detailed explanations if the user is feeling anxious or stressed. This allows new users to efficiently improve their expertise while reducing stress.

[0126] Furthermore, for expert users, the system helps them stay up-to-date by promptly notifying them of the latest research results and technological trends. The emotion engine also detects the emotional state of the expert user's work environment and suggests relaxation methods if emotions that hinder concentration arise. In this way, the present invention is a multi-functional support system that enables researchers to conduct their research efficiently in an optimal environment.

[0127] The following describes the processing flow.

[0128] Step 1:

[0129] The server accesses scientific databases and technical article sites on the internet and retrieves the necessary research information via APIs. The retrieved data is then filtered based on specific keywords.

[0130] Step 2:

[0131] The server analyzes research information acquired using natural language processing techniques. Topic modeling is utilized to extract important technology trends and keywords from the data.

[0132] Step 3:

[0133] The terminal provides an interface for receiving research topics and questions from users. Users input questions and interests related to their own research into the terminal.

[0134] Step 4:

[0135] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state at that moment. The emotion engine provides information such as whether the user is stressed or calm.

[0136] Step 5:

[0137] The server integrates user input information with data from the emotion engine and uses an AI model to propose a research process. This proposal includes experimental design and training content. This proposal is then sent to the user via the device.

[0138] Step 6:

[0139] The device provides learning materials tailored to the emotional state of new users. If a user is feeling anxious, it provides detailed explanations and materials with an adjusted pace.

[0140] Step 7:

[0141] The server notifies expert users of the latest research findings and technology trends on their devices. An emotion engine monitors the expert's emotional state and provides feedback to help them maintain focus.

[0142] Step 8:

[0143] The system records user operation logs and emotional state data on the terminal and sends them to the server. The server uses this data to update the organization's knowledge database and utilize it for future research and education.

[0144] (Example 2)

[0145] 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".

[0146] Traditional research support systems require the collection and analysis of large amounts of data, but lack adaptive support tailored to the user's emotional state. Furthermore, when novice and expert users receive the same information, the depth and speed of that information are often inappropriate. In addition, the lack of a mechanism for systematically accumulating and utilizing collected knowledge hinders efficient research activities.

[0147] 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.

[0148] In this invention, the server includes means for collecting research information, means for analyzing the information using analytical techniques, and means for proposing a research process to the user based on the analysis results. This makes it possible to provide information optimized by expertise while taking into account the user's emotional state. Furthermore, it realizes a system that enables efficient accumulation and sharing of knowledge within the organization.

[0149] "Research information" refers to information such as data, literature, and articles related to scientific investigations and technical analyses.

[0150] "Analytical techniques" refer to a set of methods and technologies for processing collected data and extracting meaningful information and trends.

[0151] "Users" refer to individuals with diverse knowledge levels, such as experts and newcomers, who use the system for research activities.

[0152] "Emotional state" refers to the psychological condition exhibited by the user, and includes emotions detected from facial expressions, voice, etc.

[0153] "Educational materials" refer to teaching materials and reference materials provided to support users' learning and improvement of their expertise.

[0154] "Expertise" refers to the state of possessing a high level of knowledge and skills in a particular field.

[0155] A "wide-area communication network" refers to widely used communication networks such as the internet, which provide an environment where diverse information sources can be accessed.

[0156] An "interface" is a technology that refers to the boundary or point of contact used when a user and a system exchange information.

[0157] "Question-and-answer format questions" refers to interactive formats that include quizzes and questions provided to check the user's understanding.

[0158] "Summary of related literature" refers to summary information that extracts important information from multiple sources and provides it in a shortened format.

[0159] This invention is a system aimed at the efficient collection and analysis of research information and the optimization of the user experience based on emotions. The system mainly consists of a server, terminals, and an emotion engine.

[0160] The server accesses diverse data sources on a wide-area communication network and collects research information using interfaces. Specifically, it retrieves information from databases and article domains on the internet. This information is then analyzed using analytical techniques. The server implements natural language processing libraries using Python and Java (registered trademark) to break down the collected data into topics and extract important technology trends. This process enables the efficient provision of the technology information that users need.

[0161] The terminal is responsible for the user interface. When the user inputs a research topic or question, this information is sent to the server, and based on the analysis results and the sentiment engine's judgment, personalized suggestions are provided to the user. Frameworks such as React and Angular are used to build the user interface and enhance usability.

[0162] The emotion engine is responsible for detecting the user's emotional state and personalizing the experience. Specifically, it includes a cloud-based speech recognition API for analyzing voice input and image processing technology used for facial expression analysis. This allows for the real-time detection of user anxiety and confusion, enabling the presentation of information and adjustment of the learning pace accordingly.

[0163] For example, if a user uses the system to learn the "fundamentals of quantum computing," the server aggregates and analyzes relevant academic information. The terminal then provides optimal information while considering the user's emotional state. If the user shows signs of impatience, the emotion engine detects this and adjusts the content to make the explanation easier to understand. An example of a prompt in this case would be, "Please provide a concise explanation of the fundamentals of quantum computing. Please also provide more detailed information depending on the user's level of understanding."

[0164] Thus, the present invention is a new form of research support system that enables the provision of information tailored to the diverse needs of users, as well as the accumulation and sharing of knowledge.

[0165] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0166] Step 1:

[0167] The server receives research topics and questions entered by the user. Based on this input, it accesses multiple information sources on a wide-area communication network through the interface and collects relevant research information. Specifically, the server uses keywords to send queries to databases and article areas via APIs and retrieves highly relevant results. The output is a collection of raw data related to the target research topic.

[0168] Step 2:

[0169] The server analyzes collected research information using natural language processing techniques. It parses and tokenizes the raw input data. Furthermore, it utilizes machine learning models to extract topics and perform trend analysis. Specifically, it performs language analysis using Python's natural language processing library and clustering using a generative AI model. The output obtained from this process is a summary of analyzed and classified technology trends and themes.

[0170] Step 3:

[0171] The terminal sends analysis results from the server and emotional state data entered by the user to the emotion engine. The input consists of facial expressions and voice data shown by the user to the terminal, and the emotion engine uses this to determine the emotional state. The operation involves analysis using facial recognition software and emotion estimation using a voice recognition API. The output is evaluation data that quantifies the user's emotional state.

[0172] Step 4:

[0173] The terminal integrates output from the emotion engine with server analysis results to provide a research process and information presentation optimized for the user. The input is integrated data, and its specific actions include visualization and information organization through the user interface. Through this process, the user receives information adjusted according to their level of understanding and emotions.

[0174] Step 5:

[0175] Users advance their research activities based on optimization information provided by the device. Specifically, this includes actions taken using presented prompts and technology trends. The input is information suggestions from the device, and the output obtained by the user is new insights and practical results.

[0176] Step 6:

[0177] The terminal collects user feedback and sends it to the server. Inputs include user ratings and comments, and specific actions include using rating forms and feedback widgets. The server then stores this data back into a database for further improvement and analysis. The output is quantified data of insights and experience that helps improve the system.

[0178] (Application Example 2)

[0179] 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 device 14 will be referred to as the "terminal."

[0180] Many brick-and-mortar stores face the challenge of declining customer satisfaction and purchasing intent due to insufficient personalized product recommendations and information provision for each individual customer. Furthermore, in fields requiring specialized knowledge, the collection and analysis of research information is time-consuming, necessitating more efficient processes.

[0181] 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.

[0182] In this invention, the server includes means for collecting research information, means for analyzing the collected research information using natural language processing technology, and means for recognizing the customer's emotional state and providing a personalized in-store experience. This enables product suggestions tailored to the customer's emotions, provides researchers with efficient information collection and analysis, and improves satisfaction for both parties.

[0183] "Means of collecting research information" refers to the general term for methods and equipment used to access scientific databases and technical article websites and obtain necessary information.

[0184] "Natural language processing technology" refers to a series of technologies that enable computers to understand human language and analyze its meaning.

[0185] "Means of proposing research processes" refers to methods of showing users how to conduct research efficiently based on the information collected.

[0186] "Means of providing learning materials" refers to methods of preparing materials to assist new users in acquiring knowledge and skills.

[0187] A "means of notifying users of the latest research results and technological trends" refers to a system that keeps users informed so they can always access new information.

[0188] "Means for recording knowledge and thought processes" refers to methods for saving users' technical knowledge and ideas and making them shareable within an organization.

[0189] "Means of recognizing emotional states" refers to technologies that analyze a customer's facial expressions and voice to understand their current psychological state.

[0190] "Means of providing personalized experiences" refers to methods for tailoring and delivering information and services precisely according to the individual needs and emotions of each customer.

[0191] "Methods for making product recommendations" refer to techniques for recommending appropriate products based on the customer's interests and feelings.

[0192] This system consists of a server, a user terminal, and an emotion recognition engine. The server accesses databases and article sites on the internet and retrieves research information using APIs. This information is analyzed using natural language processing techniques to extract specific trends and necessary content. The server also utilizes generative AI models to generate personalized suggestions tailored to the user's emotional state.

[0193] User terminals are devices such as smartphones and tablets used in stores, and they analyze customer emotions through facial recognition and voice input. For this purpose, the terminals are equipped with cameras and microphones, and open-source facial recognition libraries and voice recognition engines are installed.

[0194] Based on the emotional data the system has gathered, it proposes the most suitable products and services to customers. Specifically, it inputs prompts such as, "Customer appears unsure. Generate a friendly guide to assist in choosing the perfect product based on their preferences and previous shopping history," into the generating AI model, which then generates appropriate guidance.

[0195] For example, if a customer finds an item they're interested in in the store but wants more detailed information, this system can quickly provide rich content and details. In this way, it can improve customer satisfaction and purchasing intent while also reducing the workload on staff.

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

[0197] Step 1:

[0198] The server accesses databases and article sites on the internet. It uses APIs to retrieve research information. The input is a search query based on the user's research topic and interests, and the output is a list of specific information. This information serves as raw material for subsequent natural language processing.

[0199] Step 2:

[0200] The server uses natural language processing techniques on the acquired information list to extract technology trends and useful information. In this process, a text analysis algorithm analyzes the input data to extract keywords and identify trends. The output is an abstracted set of information resulting from the analysis.

[0201] Step 3:

[0202] The device uses a camera and microphone to collect facial expressions and audio data of customers in the store. The input is specific visual and audio data, and the output is the result of an emotional state evaluation by an emotion recognition engine. This evaluation result is used to make personalized suggestions in the next step.

[0203] Step 4:

[0204] The server inputs prompt sentences generated based on emotional states and research information into the generating AI model. Specifically, it generates prompt sentences such as, "Customer appears unsure. Generate a friendly guide to assist in choosing the perfect product based on their preferences and previous shopping history," and instructs the AI. The output is guidance and suggestions tailored to the customer's needs.

[0205] Step 5:

[0206] The user terminal receives responses from the AI ​​and presents them to the customer. The input is the AI's suggestions, and the output is information provided through the user interface. Specifically, this includes on-screen recommendations and voice guidance. In this step, the customer's purchasing decision is supported by viewing and listening to the suggestions.

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

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

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

[0210] [Second Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0223] This invention is implemented as a system for streamlining the research and development process using AI. The system consists of a server, a terminal, and a user interface.

[0224] The server connects to online scientific paper databases and technical article websites, automatically collecting necessary research information via APIs. The collected data is analyzed on the server using natural language processing technology to extract important information and trends. This process allows for efficient understanding of the latest research trends.

[0225] The terminal acts as the interface with the user, receiving research topics and questions from the user. Users can input questions or topics related to a specific research field and receive research processes suggested by the server based on that input. The terminal also provides learning materials from the server to new users, supporting their professional development. These learning materials include foundational knowledge in related fields and quiz-style training to help new users deepen their understanding.

[0226] For expert users, the server notifies them of the latest research findings and technological trends analyzed by the server. This allows experts to easily access the latest information. The terminal also records the user's actions and thought processes and sends this data to the server. This data is stored in the organization's database and used for future projects and researcher training.

[0227] As a concrete example, when a junior chemistry researcher (user) is working on synthesizing a new material, they can receive summaries of relevant literature and experimental design suggestions from the server via their terminal. This allows the user to proceed with their research with confidence and improve their expertise in a short period of time. Furthermore, expert users can quickly determine the direction of their research based on information on new synthesis methods and technological trends provided by the server. In this way, the present invention effectively functions as a system that improves the productivity of researchers and contributes to the advancement of technology.

[0228] The following describes the processing flow.

[0229] Step 1:

[0230] The server accesses online scientific paper databases and technical article websites, using APIs to collect relevant research information. The collected information is then filtered based on specific keywords or queries.

[0231] Step 2:

[0232] The server analyzes the research information it collects using natural language processing techniques. Topic modeling and keyword extraction are used to identify important technological trends and developments within the data.

[0233] Step 3:

[0234] The terminal receives research topics and questions from the user. The user inputs specific questions or interests related to their research, and that information is sent to the server.

[0235] Step 4:

[0236] The server uses an AI model to propose a research process based on the user's input. Specifically, it generates recommendations including appropriate experimental design and research flow, and sends them to the terminal.

[0237] Step 5:

[0238] The device displays learning materials for new users based on output from an AI model. These materials include summaries of basic knowledge and assessments in the form of quizzes.

[0239] Step 6:

[0240] The server summarizes the latest research findings and technological trends and notifies expert users of their terminals. This allows experts to easily access the latest information and quickly decide on the direction of their research.

[0241] Step 7:

[0242] The user records their technical insights and thought processes from their research on a device. The device sends this data to a server, where it is stored in the organization's knowledge database.

[0243] (Example 1)

[0244] 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."

[0245] Traditional research and development processes required manually searching and analyzing vast amounts of literature and materials, which was a significant burden in terms of time and effort. Furthermore, for junior researchers lacking specialized knowledge, support systems for rapidly improving their expertise were insufficient, and opportunities to access the latest research results were limited. This hindered the efficiency and accuracy of research, leading to a slower pace of technological innovation.

[0246] 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.

[0247] In this invention, the server includes a device for collecting research data, a device for analyzing the collected research data using natural language processing technology, and a device for extracting important information and trends from the analyzed data using a generative AI model. This enables efficient handling of large amounts of research data, extraction of important information, and proposal of research processes. Furthermore, it is possible to significantly improve research efficiency and the speed of technological innovation by providing educational materials to new researchers, including basic knowledge of related fields and quizzes, and by immediately notifying experts of the latest research results.

[0248] "Research data" refers to a broad collection of knowledge encompassing information and materials gathered for scientific investigation and technological innovation.

[0249] "Natural language processing technology" refers to technologies for recognizing, understanding, and analyzing human language using computers, and includes methods such as text mining and sentiment analysis.

[0250] A "generative AI model" is an algorithm that uses artificial intelligence technology to learn from large amounts of data and generate natural-sounding text, similar to what humans would write.

[0251] "Educational materials" refer to information and content provided to improve users' expertise, including basic knowledge, quizzes, and summaries of related materials.

[0252] "Important information and trends" refer to meaningful insights and data patterns that indicate progress in research and technological trends.

[0253] "Internet information sources" refer to sources of information accessible via the network, such as websites, databases, and online articles and papers.

[0254] "Operation history" refers to a record of actions and inputs made by a user within the system, and is data used for analysis based on that history.

[0255] This invention is a system for streamlining the research and development process, consisting of a server, terminals, and users. The server is responsible for collecting research data and analyzing it using natural language processing techniques and generative AI models. High-performance servers are required as hardware, and the software includes a database management system, natural language processing libraries, and a framework for running generative AI models.

[0256] The server connects to information sources on the internet and automatically retrieves relevant research data via APIs. This data is analyzed using natural language processing techniques to extract important information and trends. Based on these results, the server proposes research methods to the user.

[0257] On the other hand, the terminal functions as an interface between the user and the server, displaying information and suggestions from the server to the user. Users can receive suggestions from the server by entering specific research topics or questions through the terminal. Educational materials designed for users are provided on the terminal to support the development of new users' expertise. These educational materials include quizzes to deepen basic knowledge and understanding of related fields.

[0258] For example, if a junior chemistry researcher enters the prompt message, "I want to know the latest trends in synthesis methods for new materials," the server generates summaries of relevant literature and proposed experimental designs, which are then displayed on the terminal. In this way, the entire system operates in an integrated manner, streamlining the research and development process and promoting the improvement of the user's knowledge.

[0259] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0260] Step 1:

[0261] The server connects to multiple information sources on the internet and collects research data using APIs. Specifically, the server searches for information sources using specified keywords and stores the retrieved data in a database on the server. The input is the specified keywords and search conditions, and the output is the research data retrieved from the information sources.

[0262] Step 2:

[0263] The server analyzes the collected research data using natural language processing techniques. The server extracts important information and trends from the data using text analysis methods. This process utilizes a generative AI model to generate summaries of relevant papers and articles. The input is the collected research data, and the output is the extracted information and summaries.

[0264] Step 3:

[0265] The terminal displays the analysis results provided by the server to the user. The user can input any prompt text through the terminal, and based on that, will receive suitable suggestions from the server. For example, if a prompt text such as "Please tell me the synthesis method for the new material" is entered, the server will provide information based on the analysis results. The input is the prompt text from the user, and the output is suggestions or information based on the analysis results.

[0266] Step 4:

[0267] The device provides users with educational materials to enhance their expertise. The device displays learning content, including foundational knowledge and quizzes tailored to the user's experience and knowledge level. Input is the user's profile and knowledge level, while output is appropriately customized educational material.

[0268] Step 5:

[0269] The server notifies expert users of the latest research findings and technological trends. Expert users receive these notifications at all times via their terminals and can check detailed information as needed. Inputs are the latest analysis results and the user's areas of interest, and outputs are notifications to expert users.

[0270] Step 6:

[0271] The terminal records the user's operation history and thought process, and sends this data to a server. The server analyzes this data and stores it in the organization's database. The input is the user's operation history and reactions, and the output is the analyzed insights and accumulated knowledge data.

[0272] (Application Example 1)

[0273] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0274] In modern manufacturing, rapidly changing technological information and the frequent introduction of new materials necessitate the optimization of manufacturing processes. However, information acquisition and analysis are often done manually, leading to challenges such as delays in efficient process improvement and decision-making. Furthermore, training new employees is time-consuming and costly, making it difficult to cultivate them into immediately productive members of the workforce. A system is needed to solve these problems and maximize the efficiency of manufacturing processes.

[0275] 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.

[0276] In this invention, the server includes means for collecting research information, means for analyzing the collected research information using natural language processing technology, and means for collecting technical information for improving efficiency in the manufacturing process and optimizing its operation based on that information. This enables the immediate incorporation of the latest technologies into the manufacturing line and rapid and effective process optimization. Furthermore, it is possible to improve the overall technical knowledge of the organization by providing learning materials to support the improvement of expertise for new employees and notifying expert users of the latest research results and technological trends.

[0277] "Research information" refers to knowledge obtained from scientific and technological papers, articles, and databases.

[0278] "Natural language processing technology" is an artificial intelligence technology that analyzes text data and extracts important information.

[0279] A "manufacturing process" is a set of steps and procedures necessary to complete a product.

[0280] "Efficiency optimization" is an optimization process aimed at achieving maximum results while minimizing resources and time.

[0281] "Technical information" refers to the latest knowledge regarding new technologies, methods, and materials.

[0282] "Optimizing operation" means making adjustments to maximize the performance of a system, machine, or process.

[0283] A "new user" refers to a user who has recently joined a particular field or organization.

[0284] The "learning materials to support the improvement of expertise" refer to educational materials provided to assist in the acquisition of specific technologies and specialized knowledge.

[0285] The "expert user" refers to a user with advanced knowledge and experience in a specific field.

[0286] The "latest research results and technological trends" refer to information indicating the most recent discoveries and developing directions in current science and technology.

[0287] "Accumulating knowledge" means organizing experiences and information and storing them in a form that can be utilized in the future.

[0288] The server collects research information and performs analysis using natural language processing technology. The server accesses databases and technical article sites on the Internet through APIs to obtain the latest technical information. The acquired information is stored in a database, and important information and technological trends are extracted by natural language processing. As a result, users can quickly obtain the information necessary for optimizing the manufacturing process.

[0289] The terminal functions as an interface with the user. Users can receive research procedures and proposals for the latest technologies through the terminal. In addition, the terminal provides learning materials to support the improvement of expertise for new users and supports learning through quiz-style training and summaries of relevant literature. Expert users are notified of the latest research results and technological trends analyzed by the server, which helps to optimize the manufacturing process efficiently and effectively.

[0290] Users can use this system to share technical knowledge and thinking processes, strengthening the knowledge base of the entire organization. This data is utilized in future projects and the education of new employees.

[0291] For example, if a manufacturing plant plans to introduce a new material, the server collects and analyzes relevant technical information and provides the user with optimal manufacturing procedures and improvement suggestions via a terminal. This allows the plant to quickly begin manufacturing using the properties of the new material.

[0292] An example of a prompt to input into a generative AI model is: "Suggest ways to improve the efficiency of a manufacturing line using AI. How will you collect and analyze information on the latest manufacturing technologies and materials?"

[0293] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0294] Step 1:

[0295] The server accesses databases and article sites on the internet via APIs to retrieve the latest research information. The input consists of URLs of the information sources to be collected and query conditions, while the output includes the retrieved text data. This data is then prepared within the server for the following processing.

[0296] Step 2:

[0297] The server performs analysis on the acquired text data using natural language processing techniques. The input is the text data acquired in the previous step, and the output extracts important information and technology trends. Specific operations include text tokenization, keyword extraction, and topic modeling.

[0298] Step 3:

[0299] The server generates technical information for efficiency improvements based on the analysis results and sends it to the terminal. The inputs used are extracted key information and technology trends, while the output includes optimization suggestions and improvement measures. This operation enables the provision of concrete suggestions to the user.

[0300] Step 4:

[0301] The terminal displays the technical information and improvement measures proposed by the user so that they can be confirmed through the interface. As input, there is technical information sent from the server, and as output, it is presented as visual information that the user can view on the screen. Based on this, the user obtains guidelines for improving the manufacturing process.

[0302] Step 5:

[0303] The user utilizes the learning materials provided by the terminal and improves their expertise through quizzes and literature summaries. The input includes specific learning themes or fields, and the output aims to improve the user's knowledge. As specific operations, interactive quizzes and summary displays of relevant literature are conducted.

[0304] Step 6:

[0305] Expert users receive notifications of the latest research results and technological trends analyzed by the server through the terminal. As input, there are the latest analysis results, and as output, the information is included as a notification. Through this operation, it becomes possible for the user to quickly obtain the information necessary for improving the manufacturing process.

[0306] Step 7:

[0307] The server records the user's operations and thought processes, and accumulates the obtained data in the organization's database. The input includes the user's behavior data and feedback, and the output includes the accumulated knowledge data. Through this process, the overall knowledge base of the organization is strengthened.

[0308] Furthermore, an emotion engine for estimating the user's emotions may be combined. That is, the specific processing unit 290 may estimate the user's emotions using the emotion identification model 59 and perform specific processing using the user's emotions.

[0309] This invention is implemented in a form that combines a system for streamlining the research and development process with an emotion engine that recognizes user emotions. This system consists of a server, a terminal, and an emotion engine.

[0310] The server accesses scientific databases and technology article sites on the internet, collecting research information via APIs. The server analyzes this information using natural language processing techniques to identify important technology trends. This enables the efficient collection and analysis of information necessary for research.

[0311] The terminal acts as the interface with the user, receiving research topics and questions from the user. Based on information sent from the server and the analysis results from the emotion engine, the terminal proposes an optimized research process for the user. The emotion engine analyzes the user's facial expressions and voice input to determine their emotional state, and uses that data to personalize the user's experience.

[0312] As a concrete example, when a new user uses a terminal to learn about a new experimental technique, the server collects relevant information and proposes an experimental process based on it. At the same time, an emotion engine monitors the user's emotional state and adjusts the content to provide slower, more detailed explanations if the user is feeling anxious or stressed. This allows new users to efficiently improve their expertise while reducing stress.

[0313] Furthermore, for expert users, the system helps them stay up-to-date by promptly notifying them of the latest research results and technological trends. The emotion engine also detects the emotional state of the expert user's work environment and suggests relaxation methods if emotions that hinder concentration arise. In this way, the present invention is a multi-functional support system that enables researchers to conduct their research efficiently in an optimal environment.

[0314] The following describes the processing flow.

[0315] Step 1:

[0316] The server accesses scientific databases and technical article sites on the internet and retrieves the necessary research information via APIs. The retrieved data is then filtered based on specific keywords.

[0317] Step 2:

[0318] The server analyzes research information acquired using natural language processing techniques. Topic modeling is utilized to extract important technology trends and keywords from the data.

[0319] Step 3:

[0320] The terminal provides an interface for receiving research topics and questions from users. Users input questions and interests related to their own research into the terminal.

[0321] Step 4:

[0322] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state at that moment. The emotion engine provides information such as whether the user is stressed or calm.

[0323] Step 5:

[0324] The server integrates user input information with data from the emotion engine and uses an AI model to propose a research process. This proposal includes experimental design and training content. This proposal is then sent to the user via the device.

[0325] Step 6:

[0326] The device provides learning materials tailored to the emotional state of new users. If a user is feeling anxious, it provides detailed explanations and materials with an adjusted pace.

[0327] Step 7:

[0328] The server notifies expert users of the latest research findings and technology trends on their devices. An emotion engine monitors the expert's emotional state and provides feedback to help them maintain focus.

[0329] Step 8:

[0330] The system records user operation logs and emotional state data on the terminal and sends them to the server. The server uses this data to update the organization's knowledge database and utilize it for future research and education.

[0331] (Example 2)

[0332] 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".

[0333] Traditional research support systems require the collection and analysis of large amounts of data, but lack adaptive support tailored to the user's emotional state. Furthermore, when novice and expert users receive the same information, the depth and speed of that information are often inappropriate. In addition, the lack of a mechanism for systematically accumulating and utilizing collected knowledge hinders efficient research activities.

[0334] 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.

[0335] In this invention, the server includes means for collecting research information, means for analyzing the information using analytical techniques, and means for proposing a research process to the user based on the analysis results. This makes it possible to provide information optimized by expertise while taking into account the user's emotional state. Furthermore, it realizes a system that enables efficient accumulation and sharing of knowledge within the organization.

[0336] "Research information" refers to information such as data, literature, and articles related to scientific investigations and technical analyses.

[0337] "Analytical techniques" refer to a set of methods and technologies for processing collected data and extracting meaningful information and trends.

[0338] "Users" refer to individuals with diverse knowledge levels, such as experts and newcomers, who use the system for research activities.

[0339] "Emotional state" refers to the psychological condition exhibited by the user, and includes emotions detected from facial expressions, voice, etc.

[0340] "Educational materials" refer to teaching materials and reference materials provided to support users' learning and improvement of their expertise.

[0341] "Expertise" refers to the state of possessing a high level of knowledge and skills in a particular field.

[0342] A "wide-area communication network" refers to widely used communication networks such as the internet, which provide an environment where diverse information sources can be accessed.

[0343] An "interface" is a technology that refers to the boundary or point of contact used when a user and a system exchange information.

[0344] "Question-and-answer format questions" refers to interactive formats that include quizzes and questions provided to check the user's understanding.

[0345] "Summary of related literature" refers to summary information that extracts important information from multiple sources and provides it in a shortened format.

[0346] This invention is a system aimed at the efficient collection and analysis of research information and the optimization of the user experience based on emotions. The system mainly consists of a server, terminals, and an emotion engine.

[0347] The server accesses diverse data sources on a wide-area communication network and collects research information using interfaces. Specifically, it retrieves information from databases and article databases on the internet. This information is then analyzed using analytical techniques. The server implements natural language processing libraries using Python and Java to break down the collected data into topics and extract important technology trends. This process enables the efficient provision of the technology information that users need.

[0348] The terminal is responsible for the user interface. When the user inputs a research topic or question, this information is sent to the server, and based on the analysis results and the sentiment engine's judgment, personalized suggestions are provided to the user. Frameworks such as React and Angular are used to build the user interface and enhance usability.

[0349] The emotion engine is responsible for detecting the user's emotional state and personalizing the experience. Specifically, it includes a cloud-based speech recognition API for analyzing voice input and image processing technology used for facial expression analysis. This allows for the real-time detection of user anxiety and confusion, enabling the presentation of information and adjustment of the learning pace accordingly.

[0350] For example, if a user uses the system to learn the "fundamentals of quantum computing," the server aggregates and analyzes relevant academic information. The terminal then provides optimal information while considering the user's emotional state. If the user shows signs of impatience, the emotion engine detects this and adjusts the content to make the explanation easier to understand. An example of a prompt in this case would be, "Please provide a concise explanation of the fundamentals of quantum computing. Please also provide more detailed information depending on the user's level of understanding."

[0351] Thus, the present invention is a new form of research support system that enables the provision of information tailored to the diverse needs of users, as well as the accumulation and sharing of knowledge.

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

[0353] Step 1:

[0354] The server receives research topics and questions entered by the user. Based on this input, it accesses multiple information sources on a wide-area communication network through the interface and collects relevant research information. Specifically, the server uses keywords to send queries to databases and article areas via APIs and retrieves highly relevant results. The output is a collection of raw data related to the target research topic.

[0355] Step 2:

[0356] The server analyzes collected research information using natural language processing techniques. It parses and tokenizes the raw input data. Furthermore, it utilizes machine learning models to extract topics and perform trend analysis. Specifically, it performs language analysis using Python's natural language processing library and clustering using a generative AI model. The output obtained from this process is a summary of analyzed and classified technology trends and themes.

[0357] Step 3:

[0358] The terminal sends analysis results from the server and emotional state data entered by the user to the emotion engine. The input consists of facial expressions and voice data shown by the user to the terminal, and the emotion engine uses this to determine the emotional state. The operation involves analysis using facial recognition software and emotion estimation using a voice recognition API. The output is evaluation data that quantifies the user's emotional state.

[0359] Step 4:

[0360] The terminal integrates output from the emotion engine with server analysis results to provide a research process and information presentation optimized for the user. The input is integrated data, and its specific actions include visualization and information organization through the user interface. Through this process, the user receives information adjusted according to their level of understanding and emotions.

[0361] Step 5:

[0362] Users advance their research activities based on optimization information provided by the device. Specifically, this includes actions taken using presented prompts and technology trends. The input is information suggestions from the device, and the output obtained by the user is new insights and practical results.

[0363] Step 6:

[0364] The terminal collects user feedback and sends it to the server. Inputs include user ratings and comments, and specific actions include using rating forms and feedback widgets. The server then stores this data back into a database for further improvement and analysis. The output is quantified data of insights and experience that helps improve the system.

[0365] (Application Example 2)

[0366] 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 as the "terminal".

[0367] Many brick-and-mortar stores face the challenge of declining customer satisfaction and purchasing intent due to insufficient personalized product recommendations and information provision for each individual customer. Furthermore, in fields requiring specialized knowledge, the collection and analysis of research information is time-consuming, necessitating more efficient processes.

[0368] 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.

[0369] In this invention, the server includes means for collecting research information, means for analyzing the collected research information using natural language processing technology, and means for recognizing the customer's emotional state and providing a personalized in-store experience. This enables product suggestions tailored to the customer's emotions, provides researchers with efficient information collection and analysis, and improves satisfaction for both parties.

[0370] "Means of collecting research information" refers to the general term for methods and equipment used to access scientific databases and technical article websites and obtain necessary information.

[0371] "Natural language processing technology" refers to a series of technologies that enable computers to understand human language and analyze its meaning.

[0372] "Means of proposing research processes" refers to methods of showing users how to conduct research efficiently based on the information collected.

[0373] "Means of providing learning materials" refers to methods of preparing materials to assist new users in acquiring knowledge and skills.

[0374] A "means of notifying users of the latest research results and technological trends" refers to a system that keeps users informed so they can always access new information.

[0375] "Means for recording knowledge and thought processes" refers to methods for saving users' technical knowledge and ideas and making them shareable within an organization.

[0376] "Means of recognizing emotional states" refers to technologies that analyze a customer's facial expressions and voice to understand their current psychological state.

[0377] "Means of providing personalized experiences" refers to methods for tailoring and delivering information and services precisely according to the individual needs and emotions of each customer.

[0378] "Methods for making product recommendations" refer to techniques for recommending appropriate products based on the customer's interests and feelings.

[0379] This system consists of a server, a user terminal, and an emotion recognition engine. The server accesses databases and article sites on the internet and retrieves research information using APIs. This information is analyzed using natural language processing techniques to extract specific trends and necessary content. The server also utilizes generative AI models to generate personalized suggestions tailored to the user's emotional state.

[0380] User terminals are devices such as smartphones and tablets used in stores, and they analyze customer emotions through facial recognition and voice input. For this purpose, the terminals are equipped with cameras and microphones, and open-source facial recognition libraries and voice recognition engines are installed.

[0381] Based on the emotional data the system has gathered, it proposes the most suitable products and services to customers. Specifically, it inputs prompts such as, "Customer appears unsure. Generate a friendly guide to assist in choosing the perfect product based on their preferences and previous shopping history," into the generating AI model, which then generates appropriate guidance.

[0382] For example, if a customer finds an item they're interested in in the store but wants more detailed information, this system can quickly provide rich content and details. In this way, it can improve customer satisfaction and purchasing intent while also reducing the workload on staff.

[0383] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0384] Step 1:

[0385] The server accesses databases and article sites on the internet. It uses APIs to retrieve research information. The input is a search query based on the user's research topic and interests, and the output is a list of specific information. This information serves as raw material for subsequent natural language processing.

[0386] Step 2:

[0387] The server uses natural language processing techniques on the acquired information list to extract technology trends and useful information. In this process, a text analysis algorithm analyzes the input data to extract keywords and identify trends. The output is an abstracted set of information resulting from the analysis.

[0388] Step 3:

[0389] The device uses a camera and microphone to collect facial expressions and audio data of customers in the store. The input is specific visual and audio data, and the output is the result of an emotional state evaluation by an emotion recognition engine. This evaluation result is used to make personalized suggestions in the next step.

[0390] Step 4:

[0391] The server inputs prompt sentences generated based on emotional states and research information into the generating AI model. Specifically, it generates prompt sentences such as, "Customer appears unsure. Generate a friendly guide to assist in choosing the perfect product based on their preferences and previous shopping history," and instructs the AI. The output is guidance and suggestions tailored to the customer's needs.

[0392] Step 5:

[0393] The user terminal receives responses from the AI ​​and presents them to the customer. The input is the AI's suggestions, and the output is information provided through the user interface. Specifically, this includes on-screen recommendations and voice guidance. In this step, the customer's purchasing decision is supported by viewing and listening to the suggestions.

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

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

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

[0397] [Third Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0410] This invention is implemented as a system for streamlining the research and development process using AI. The system consists of a server, a terminal, and a user interface.

[0411] The server connects to online scientific paper databases and technical article websites, automatically collecting necessary research information via APIs. The collected data is analyzed on the server using natural language processing technology to extract important information and trends. This process allows for efficient understanding of the latest research trends.

[0412] The terminal acts as the interface with the user, receiving research topics and questions from the user. Users can input questions or topics related to a specific research field and receive research processes suggested by the server based on that input. The terminal also provides learning materials from the server to new users, supporting their professional development. These learning materials include foundational knowledge in related fields and quiz-style training to help new users deepen their understanding.

[0413] For expert users, the server notifies them of the latest research findings and technological trends analyzed by the server. This allows experts to easily access the latest information. The terminal also records the user's actions and thought processes and sends this data to the server. This data is stored in the organization's database and used for future projects and researcher training.

[0414] As a concrete example, when a junior chemistry researcher (user) is working on synthesizing a new material, they can receive summaries of relevant literature and experimental design suggestions from the server via their terminal. This allows the user to proceed with their research with confidence and improve their expertise in a short period of time. Furthermore, expert users can quickly determine the direction of their research based on information on new synthesis methods and technological trends provided by the server. In this way, the present invention effectively functions as a system that improves the productivity of researchers and contributes to the advancement of technology.

[0415] The following describes the processing flow.

[0416] Step 1:

[0417] The server accesses online scientific paper databases and technical article websites, using APIs to collect relevant research information. The collected information is then filtered based on specific keywords or queries.

[0418] Step 2:

[0419] The server analyzes the research information it collects using natural language processing techniques. Topic modeling and keyword extraction are used to identify important technological trends and developments within the data.

[0420] Step 3:

[0421] The terminal receives research topics and questions from the user. The user inputs specific questions or interests related to their research, and that information is sent to the server.

[0422] Step 4:

[0423] The server uses an AI model to propose a research process based on the user's input. Specifically, it generates recommendations including appropriate experimental design and research flow, and sends them to the terminal.

[0424] Step 5:

[0425] The device displays learning materials for new users based on output from an AI model. These materials include summaries of basic knowledge and assessments in the form of quizzes.

[0426] Step 6:

[0427] The server summarizes the latest research findings and technological trends and notifies expert users of their terminals. This allows experts to easily access the latest information and quickly decide on the direction of their research.

[0428] Step 7:

[0429] The user records their technical insights and thought processes from their research on a device. The device sends this data to a server, where it is stored in the organization's knowledge database.

[0430] (Example 1)

[0431] 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."

[0432] Traditional research and development processes required manually searching and analyzing vast amounts of literature and materials, which was a significant burden in terms of time and effort. Furthermore, for junior researchers lacking specialized knowledge, support systems for rapidly improving their expertise were insufficient, and opportunities to access the latest research results were limited. This hindered the efficiency and accuracy of research, leading to a slower pace of technological innovation.

[0433] 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.

[0434] In this invention, the server includes a device for collecting research data, a device for analyzing the collected research data using natural language processing technology, and a device for extracting important information and trends from the analyzed data using a generative AI model. This enables efficient handling of large amounts of research data, extraction of important information, and proposal of research processes. Furthermore, it is possible to significantly improve research efficiency and the speed of technological innovation by providing educational materials to new researchers, including basic knowledge of related fields and quizzes, and by immediately notifying experts of the latest research results.

[0435] "Research data" refers to a broad collection of knowledge encompassing information and materials gathered for scientific investigation and technological innovation.

[0436] "Natural language processing technology" refers to technologies for recognizing, understanding, and analyzing human language using computers, and includes methods such as text mining and sentiment analysis.

[0437] A "generative AI model" is an algorithm that uses artificial intelligence technology to learn from large amounts of data and generate natural-sounding text, similar to what humans would write.

[0438] "Educational materials" refer to information and content provided to improve users' expertise, including basic knowledge, quizzes, and summaries of related materials.

[0439] "Important information and trends" refer to meaningful insights and data patterns that indicate progress in research and technological trends.

[0440] "Internet information sources" refer to sources of information accessible via the network, such as websites, databases, and online articles and papers.

[0441] "Operation history" refers to a record of actions and inputs made by a user within the system, and is data used for analysis based on that history.

[0442] This invention is a system for streamlining the research and development process, consisting of a server, terminals, and users. The server is responsible for collecting research data and analyzing it using natural language processing techniques and generative AI models. High-performance servers are required as hardware, and the software includes a database management system, natural language processing libraries, and a framework for running generative AI models.

[0443] The server connects to information sources on the internet and automatically retrieves relevant research data via APIs. This data is analyzed using natural language processing techniques to extract important information and trends. Based on these results, the server proposes research methods to the user.

[0444] On the other hand, the terminal functions as an interface between the user and the server, displaying information and suggestions from the server to the user. Users can receive suggestions from the server by entering specific research topics or questions through the terminal. Educational materials designed for users are provided on the terminal to support the development of new users' expertise. These educational materials include quizzes to deepen basic knowledge and understanding of related fields.

[0445] For example, if a junior chemistry researcher enters the prompt message, "I want to know the latest trends in synthesis methods for new materials," the server generates summaries of relevant literature and proposed experimental designs, which are then displayed on the terminal. In this way, the entire system operates in an integrated manner, streamlining the research and development process and promoting the improvement of the user's knowledge.

[0446] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0447] Step 1:

[0448] The server connects to multiple information sources on the internet and collects research data using APIs. Specifically, the server searches for information sources using specified keywords and stores the retrieved data in a database on the server. The input is the specified keywords and search conditions, and the output is the research data retrieved from the information sources.

[0449] Step 2:

[0450] The server analyzes the collected research data using natural language processing techniques. The server extracts important information and trends from the data using text analysis methods. This process utilizes a generative AI model to generate summaries of relevant papers and articles. The input is the collected research data, and the output is the extracted information and summaries.

[0451] Step 3:

[0452] The terminal displays the analysis results provided by the server to the user. The user can input any prompt text through the terminal, and based on that, will receive suitable suggestions from the server. For example, if a prompt text such as "Please tell me the synthesis method for the new material" is entered, the server will provide information based on the analysis results. The input is the prompt text from the user, and the output is suggestions or information based on the analysis results.

[0453] Step 4:

[0454] The device provides users with educational materials to enhance their expertise. The device displays learning content, including foundational knowledge and quizzes tailored to the user's experience and knowledge level. Input is the user's profile and knowledge level, while output is appropriately customized educational material.

[0455] Step 5:

[0456] The server notifies expert users of the latest research findings and technological trends. Expert users receive these notifications at all times via their terminals and can check detailed information as needed. Inputs are the latest analysis results and the user's areas of interest, and outputs are notifications to expert users.

[0457] Step 6:

[0458] The terminal records the user's operation history and thought process, and sends this data to a server. The server analyzes this data and stores it in the organization's database. The input is the user's operation history and reactions, and the output is the analyzed insights and accumulated knowledge data.

[0459] (Application Example 1)

[0460] 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."

[0461] In modern manufacturing, rapidly changing technological information and the frequent introduction of new materials necessitate the optimization of manufacturing processes. However, information acquisition and analysis are often done manually, leading to challenges such as delays in efficient process improvement and decision-making. Furthermore, training new employees is time-consuming and costly, making it difficult to cultivate them into immediately productive members of the workforce. A system is needed to solve these problems and maximize the efficiency of manufacturing processes.

[0462] 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.

[0463] In this invention, the server includes means for collecting research information, means for analyzing the collected research information using natural language processing technology, and means for collecting technical information for improving efficiency in the manufacturing process and optimizing its operation based on that information. This enables the immediate incorporation of the latest technologies into the manufacturing line and rapid and effective process optimization. Furthermore, it is possible to improve the overall technical knowledge of the organization by providing learning materials to support the improvement of expertise for new employees and notifying expert users of the latest research results and technological trends.

[0464] "Research information" refers to knowledge obtained from scientific and technological papers, articles, and databases.

[0465] "Natural language processing technology" is an artificial intelligence technology that analyzes text data and extracts important information.

[0466] A "manufacturing process" is a set of steps and procedures necessary to complete a product.

[0467] "Efficiency optimization" is an optimization process aimed at achieving maximum results while minimizing resources and time.

[0468] "Technical information" refers to the latest knowledge regarding new technologies, methods, and materials.

[0469] "Optimizing operation" means making adjustments to maximize the performance of a system, machine, or process.

[0470] A "new user" refers to a user who has recently joined a particular field or organization.

[0471] "Learning materials that support the improvement of expertise" refer to educational materials provided to help acquire specific skills or specialized knowledge.

[0472] An "expert user" refers to a user who possesses advanced knowledge and experience in a specific field.

[0473] "Latest research findings and technological trends" refer to information that indicates the newest discoveries and directions of development in current science and technology.

[0474] "Accumulating knowledge" means organizing experiences and information and saving them in a way that can be used in the future.

[0475] The server collects research information and performs analysis using natural language processing technology. It accesses databases and technical article sites on the internet via APIs to obtain the latest technical information. The retrieved information is stored in a database, and important information and technological trends are extracted using natural language processing. This allows users to quickly obtain the information necessary to improve the efficiency of their manufacturing processes.

[0476] The terminal functions as an interface with the user. Through the terminal, users can receive research procedures and suggestions for the latest technologies. The terminal also provides learning materials to help new users improve their expertise, supporting their learning through quiz-based training and summaries of relevant literature. Expert users are notified of the latest research results and technological trends analyzed by the server, helping them optimize manufacturing processes efficiently and effectively.

[0477] This system allows users to share technical insights and thought processes, strengthening the knowledge base across the entire organization. This data will be used for future projects and training new employees.

[0478] For example, if a manufacturing plant plans to introduce a new material, the server collects and analyzes relevant technical information and provides the user with optimal manufacturing procedures and improvement suggestions via a terminal. This allows the plant to quickly begin manufacturing using the properties of the new material.

[0479] An example of a prompt to input into a generative AI model is: "Suggest ways to improve the efficiency of a manufacturing line using AI. How will you collect and analyze information on the latest manufacturing technologies and materials?"

[0480] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0481] Step 1:

[0482] The server accesses databases and article sites on the internet via APIs to retrieve the latest research information. The input consists of URLs of the information sources to be collected and query conditions, while the output includes the retrieved text data. This data is then prepared within the server for the following processing.

[0483] Step 2:

[0484] The server performs analysis on the acquired text data using natural language processing techniques. The input is the text data acquired in the previous step, and the output extracts important information and technology trends. Specific operations include text tokenization, keyword extraction, and topic modeling.

[0485] Step 3:

[0486] The server generates technical information for efficiency improvements based on the analysis results and sends it to the terminal. The inputs used are extracted key information and technology trends, while the output includes optimization suggestions and improvement measures. This operation enables the provision of concrete suggestions to the user.

[0487] Step 4:

[0488] The terminal displays suggested technical information and improvement measures so that the user can view them through the interface. The input is technical information sent from the server, and the output is presented as visual information that the user can view on the screen. Based on this, the user obtains guidance for improving the manufacturing process.

[0489] Step 5:

[0490] Users improve their expertise through quizzes and literature summaries using learning materials provided on their devices. Input includes specific learning themes and fields, and output aims to improve the user's knowledge. Specific actions include interactive quizzes and the display of relevant literature summaries.

[0491] Step 6:

[0492] Expert users receive notifications of the latest research findings and technological trends analyzed by the server via their terminals. The input is the latest analysis results, and the output includes information in the form of notifications. This process allows users to quickly obtain the information necessary to improve their manufacturing processes.

[0493] Step 7:

[0494] The server records user actions and thought processes, and stores the obtained data in the organization's database. Inputs include user behavior data and feedback, while outputs include accumulated knowledge data. Through this process, the knowledge base of the entire organization is strengthened.

[0495] 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.

[0496] This invention is implemented in a form that combines a system for streamlining the research and development process with an emotion engine that recognizes user emotions. This system consists of a server, a terminal, and an emotion engine.

[0497] The server accesses scientific databases and technology article sites on the internet, collecting research information via APIs. The server analyzes this information using natural language processing techniques to identify important technology trends. This enables the efficient collection and analysis of information necessary for research.

[0498] The terminal acts as the interface with the user, receiving research topics and questions from the user. Based on information sent from the server and the analysis results from the emotion engine, the terminal proposes an optimized research process for the user. The emotion engine analyzes the user's facial expressions and voice input to determine their emotional state, and uses that data to personalize the user's experience.

[0499] As a concrete example, when a new user uses a terminal to learn about a new experimental technique, the server collects relevant information and proposes an experimental process based on it. At the same time, an emotion engine monitors the user's emotional state and adjusts the content to provide slower, more detailed explanations if the user is feeling anxious or stressed. This allows new users to efficiently improve their expertise while reducing stress.

[0500] Furthermore, for expert users, the system helps them stay up-to-date by promptly notifying them of the latest research results and technological trends. The emotion engine also detects the emotional state of the expert user's work environment and suggests relaxation methods if emotions that hinder concentration arise. In this way, the present invention is a multi-functional support system that enables researchers to conduct their research efficiently in an optimal environment.

[0501] The following describes the processing flow.

[0502] Step 1:

[0503] The server accesses scientific databases and technical article sites on the internet and retrieves the necessary research information via APIs. The retrieved data is then filtered based on specific keywords.

[0504] Step 2:

[0505] The server analyzes research information acquired using natural language processing techniques. Topic modeling is utilized to extract important technology trends and keywords from the data.

[0506] Step 3:

[0507] The terminal provides an interface for receiving research topics and questions from users. Users input questions and interests related to their own research into the terminal.

[0508] Step 4:

[0509] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state at that moment. The emotion engine provides information such as whether the user is stressed or calm.

[0510] Step 5:

[0511] The server integrates user input information with data from the emotion engine and uses an AI model to propose a research process. This proposal includes experimental design and training content. This proposal is then sent to the user via the device.

[0512] Step 6:

[0513] The device provides learning materials tailored to the emotional state of new users. If a user is feeling anxious, it provides detailed explanations and materials with an adjusted pace.

[0514] Step 7:

[0515] The server notifies expert users of the latest research findings and technology trends on their devices. An emotion engine monitors the expert's emotional state and provides feedback to help them maintain focus.

[0516] Step 8:

[0517] The system records user operation logs and emotional state data on the terminal and sends them to the server. The server uses this data to update the organization's knowledge database and utilize it for future research and education.

[0518] (Example 2)

[0519] 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."

[0520] Traditional research support systems require the collection and analysis of large amounts of data, but lack adaptive support tailored to the user's emotional state. Furthermore, when novice and expert users receive the same information, the depth and speed of that information are often inappropriate. In addition, the lack of a mechanism for systematically accumulating and utilizing collected knowledge hinders efficient research activities.

[0521] 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.

[0522] In this invention, the server includes means for collecting research information, means for analyzing the information using analytical techniques, and means for proposing a research process to the user based on the analysis results. This makes it possible to provide information optimized by expertise while taking into account the user's emotional state. Furthermore, it realizes a system that enables efficient accumulation and sharing of knowledge within the organization.

[0523] "Research information" refers to information such as data, literature, and articles related to scientific investigations and technical analyses.

[0524] "Analytical techniques" refer to a set of methods and technologies for processing collected data and extracting meaningful information and trends.

[0525] "Users" refer to individuals with diverse knowledge levels, such as experts and newcomers, who use the system for research activities.

[0526] "Emotional state" refers to the psychological condition exhibited by the user, and includes emotions detected from facial expressions, voice, etc.

[0527] "Educational materials" refer to teaching materials and reference materials provided to support users' learning and improvement of their expertise.

[0528] "Expertise" refers to the state of possessing a high level of knowledge and skills in a particular field.

[0529] A "wide-area communication network" refers to widely used communication networks such as the internet, which provide an environment where diverse information sources can be accessed.

[0530] An "interface" is a technology that refers to the boundary or point of contact used when a user and a system exchange information.

[0531] "Question-and-answer format questions" refers to interactive formats that include quizzes and questions provided to check the user's understanding.

[0532] "Summary of related literature" refers to summary information that extracts important information from multiple sources and provides it in a shortened format.

[0533] This invention is a system aimed at the efficient collection and analysis of research information and the optimization of the user experience based on emotions. The system mainly consists of a server, terminals, and an emotion engine.

[0534] The server accesses diverse data sources on a wide-area communication network and collects research information using interfaces. Specifically, it retrieves information from databases and article databases on the internet. This information is then analyzed using analytical techniques. The server implements natural language processing libraries using Python and Java to break down the collected data into topics and extract important technology trends. This process enables the efficient provision of the technology information that users need.

[0535] The terminal is responsible for the user interface. When the user inputs a research topic or question, this information is sent to the server, and based on the analysis results and the sentiment engine's judgment, personalized suggestions are provided to the user. Frameworks such as React and Angular are used to build the user interface and enhance usability.

[0536] The emotion engine is responsible for detecting the user's emotional state and personalizing the experience. Specifically, it includes a cloud-based speech recognition API for analyzing voice input and image processing technology used for facial expression analysis. This allows for the real-time detection of user anxiety and confusion, enabling the presentation of information and adjustment of the learning pace accordingly.

[0537] For example, if a user uses the system to learn the "fundamentals of quantum computing," the server aggregates and analyzes relevant academic information. The terminal then provides optimal information while considering the user's emotional state. If the user shows signs of impatience, the emotion engine detects this and adjusts the content to make the explanation easier to understand. An example of a prompt in this case would be, "Please provide a concise explanation of the fundamentals of quantum computing. Please also provide more detailed information depending on the user's level of understanding."

[0538] Thus, the present invention is a new form of research support system that enables the provision of information tailored to the diverse needs of users, as well as the accumulation and sharing of knowledge.

[0539] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0540] Step 1:

[0541] The server receives research topics and questions entered by the user. Based on this input, it accesses multiple information sources on a wide-area communication network through the interface and collects relevant research information. Specifically, the server uses keywords to send queries to databases and article areas via APIs and retrieves highly relevant results. The output is a collection of raw data related to the target research topic.

[0542] Step 2:

[0543] The server analyzes collected research information using natural language processing techniques. It parses and tokenizes the raw input data. Furthermore, it utilizes machine learning models to extract topics and perform trend analysis. Specifically, it performs language analysis using Python's natural language processing library and clustering using a generative AI model. The output obtained from this process is a summary of analyzed and classified technology trends and themes.

[0544] Step 3:

[0545] The terminal sends analysis results from the server and emotional state data entered by the user to the emotion engine. The input consists of facial expressions and voice data shown by the user to the terminal, and the emotion engine uses this to determine the emotional state. The operation involves analysis using facial recognition software and emotion estimation using a voice recognition API. The output is evaluation data that quantifies the user's emotional state.

[0546] Step 4:

[0547] The terminal integrates output from the emotion engine with server analysis results to provide a research process and information presentation optimized for the user. The input is integrated data, and its specific actions include visualization and information organization through the user interface. Through this process, the user receives information adjusted according to their level of understanding and emotions.

[0548] Step 5:

[0549] Users advance their research activities based on optimization information provided by the device. Specifically, this includes actions taken using presented prompts and technology trends. The input is information suggestions from the device, and the output obtained by the user is new insights and practical results.

[0550] Step 6:

[0551] The terminal collects user feedback and sends it to the server. Inputs include user ratings and comments, and specific actions include using rating forms and feedback widgets. The server then stores this data back into a database for further improvement and analysis. The output is quantified data of insights and experience that helps improve the system.

[0552] (Application Example 2)

[0553] 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."

[0554] Many brick-and-mortar stores face the challenge of declining customer satisfaction and purchasing intent due to insufficient personalized product recommendations and information provision for each individual customer. Furthermore, in fields requiring specialized knowledge, the collection and analysis of research information is time-consuming, necessitating more efficient processes.

[0555] 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.

[0556] In this invention, the server includes means for collecting research information, means for analyzing the collected research information using natural language processing technology, and means for recognizing the customer's emotional state and providing a personalized in-store experience. This enables product suggestions tailored to the customer's emotions, provides researchers with efficient information collection and analysis, and improves satisfaction for both parties.

[0557] "Means of collecting research information" refers to the general term for methods and equipment used to access scientific databases and technical article websites and obtain necessary information.

[0558] "Natural language processing technology" refers to a series of technologies that enable computers to understand human language and analyze its meaning.

[0559] "Means of proposing research processes" refers to methods of showing users how to conduct research efficiently based on the information collected.

[0560] "Means of providing learning materials" refers to methods of preparing materials to assist new users in acquiring knowledge and skills.

[0561] A "means of notifying users of the latest research results and technological trends" refers to a system that keeps users informed so they can always access new information.

[0562] "Means for recording knowledge and thought processes" refers to methods for saving users' technical knowledge and ideas and making them shareable within an organization.

[0563] "Means of recognizing emotional states" refers to technologies that analyze a customer's facial expressions and voice to understand their current psychological state.

[0564] "Means of providing personalized experiences" refers to methods for tailoring and delivering information and services precisely according to the individual needs and emotions of each customer.

[0565] "Methods for making product recommendations" refer to techniques for recommending appropriate products based on the customer's interests and feelings.

[0566] This system consists of a server, a user terminal, and an emotion recognition engine. The server accesses databases and article sites on the internet and retrieves research information using APIs. This information is analyzed using natural language processing techniques to extract specific trends and necessary content. The server also utilizes generative AI models to generate personalized suggestions tailored to the user's emotional state.

[0567] User terminals are devices such as smartphones and tablets used in stores, and they analyze customer emotions through facial recognition and voice input. For this purpose, the terminals are equipped with cameras and microphones, and open-source facial recognition libraries and voice recognition engines are installed.

[0568] Based on the emotional data the system has gathered, it proposes the most suitable products and services to customers. Specifically, it inputs prompts such as, "Customer appears unsure. Generate a friendly guide to assist in choosing the perfect product based on their preferences and previous shopping history," into the generating AI model, which then generates appropriate guidance.

[0569] For example, if a customer finds an item they're interested in in the store but wants more detailed information, this system can quickly provide rich content and details. In this way, it can improve customer satisfaction and purchasing intent while also reducing the workload on staff.

[0570] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0571] Step 1:

[0572] The server accesses databases and article sites on the internet. It uses APIs to retrieve research information. The input is a search query based on the user's research topic and interests, and the output is a list of specific information. This information serves as raw material for subsequent natural language processing.

[0573] Step 2:

[0574] The server uses natural language processing techniques on the acquired information list to extract technology trends and useful information. In this process, a text analysis algorithm analyzes the input data to extract keywords and identify trends. The output is an abstracted set of information resulting from the analysis.

[0575] Step 3:

[0576] The device uses a camera and microphone to collect facial expressions and audio data of customers in the store. The input is specific visual and audio data, and the output is the result of an emotional state evaluation by an emotion recognition engine. This evaluation result is used to make personalized suggestions in the next step.

[0577] Step 4:

[0578] The server inputs prompt sentences generated based on emotional states and research information into the generating AI model. Specifically, it generates prompt sentences such as, "Customer appears unsure. Generate a friendly guide to assist in choosing the perfect product based on their preferences and previous shopping history," and instructs the AI. The output is guidance and suggestions tailored to the customer's needs.

[0579] Step 5:

[0580] The user terminal receives responses from the AI ​​and presents them to the customer. The input is the AI's suggestions, and the output is information provided through the user interface. Specifically, this includes on-screen recommendations and voice guidance. In this step, the customer's purchasing decision is supported by viewing and listening to the suggestions.

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

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

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

[0584] [Fourth Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

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

[0598] This invention is implemented as a system for streamlining the research and development process using AI. The system consists of a server, a terminal, and a user interface.

[0599] The server connects to online scientific paper databases and technical article websites, automatically collecting necessary research information via APIs. The collected data is analyzed on the server using natural language processing technology to extract important information and trends. This process allows for efficient understanding of the latest research trends.

[0600] The terminal acts as the interface with the user, receiving research topics and questions from the user. Users can input questions or topics related to a specific research field and receive research processes suggested by the server based on that input. The terminal also provides learning materials from the server to new users, supporting their professional development. These learning materials include foundational knowledge in related fields and quiz-style training to help new users deepen their understanding.

[0601] For expert users, the server notifies them of the latest research findings and technological trends analyzed by the server. This allows experts to easily access the latest information. The terminal also records the user's actions and thought processes and sends this data to the server. This data is stored in the organization's database and used for future projects and researcher training.

[0602] As a concrete example, when a junior chemistry researcher (user) is working on synthesizing a new material, they can receive summaries of relevant literature and experimental design suggestions from the server via their terminal. This allows the user to proceed with their research with confidence and improve their expertise in a short period of time. Furthermore, expert users can quickly determine the direction of their research based on information on new synthesis methods and technological trends provided by the server. In this way, the present invention effectively functions as a system that improves the productivity of researchers and contributes to the advancement of technology.

[0603] The following describes the processing flow.

[0604] Step 1:

[0605] The server accesses online scientific paper databases and technical article websites, using APIs to collect relevant research information. The collected information is then filtered based on specific keywords or queries.

[0606] Step 2:

[0607] The server analyzes the research information it collects using natural language processing techniques. Topic modeling and keyword extraction are used to identify important technological trends and developments within the data.

[0608] Step 3:

[0609] The terminal receives research topics and questions from the user. The user inputs specific questions or interests related to their research, and that information is sent to the server.

[0610] Step 4:

[0611] The server uses an AI model to propose a research process based on the user's input. Specifically, it generates recommendations including appropriate experimental design and research flow, and sends them to the terminal.

[0612] Step 5:

[0613] The device displays learning materials for new users based on output from an AI model. These materials include summaries of basic knowledge and assessments in the form of quizzes.

[0614] Step 6:

[0615] The server summarizes the latest research findings and technological trends and notifies expert users of their terminals. This allows experts to easily access the latest information and quickly decide on the direction of their research.

[0616] Step 7:

[0617] The user records their technical insights and thought processes from their research on a device. The device sends this data to a server, where it is stored in the organization's knowledge database.

[0618] (Example 1)

[0619] 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".

[0620] Traditional research and development processes required manually searching and analyzing vast amounts of literature and materials, which was a significant burden in terms of time and effort. Furthermore, for junior researchers lacking specialized knowledge, support systems for rapidly improving their expertise were insufficient, and opportunities to access the latest research results were limited. This hindered the efficiency and accuracy of research, leading to a slower pace of technological innovation.

[0621] 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.

[0622] In this invention, the server includes a device for collecting research data, a device for analyzing the collected research data using natural language processing technology, and a device for extracting important information and trends from the analyzed data using a generative AI model. This enables efficient handling of large amounts of research data, extraction of important information, and proposal of research processes. Furthermore, it is possible to significantly improve research efficiency and the speed of technological innovation by providing educational materials to new researchers, including basic knowledge of related fields and quizzes, and by immediately notifying experts of the latest research results.

[0623] "Research data" refers to a broad collection of knowledge encompassing information and materials gathered for scientific investigation and technological innovation.

[0624] "Natural language processing technology" refers to technologies for recognizing, understanding, and analyzing human language using computers, and includes methods such as text mining and sentiment analysis.

[0625] A "generative AI model" is an algorithm that uses artificial intelligence technology to learn from large amounts of data and generate natural-sounding text, similar to what humans would write.

[0626] "Educational materials" refer to information and content provided to improve users' expertise, including basic knowledge, quizzes, and summaries of related materials.

[0627] "Important information and trends" refer to meaningful insights and data patterns that indicate progress in research and technological trends.

[0628] "Internet information sources" refer to sources of information accessible via the network, such as websites, databases, and online articles and papers.

[0629] "Operation history" refers to a record of actions and inputs made by a user within the system, and is data used for analysis based on that history.

[0630] This invention is a system for streamlining the research and development process, consisting of a server, terminals, and users. The server is responsible for collecting research data and analyzing it using natural language processing techniques and generative AI models. High-performance servers are required as hardware, and the software includes a database management system, natural language processing libraries, and a framework for running generative AI models.

[0631] The server connects to information sources on the internet and automatically retrieves relevant research data via APIs. This data is analyzed using natural language processing techniques to extract important information and trends. Based on these results, the server proposes research methods to the user.

[0632] On the other hand, the terminal functions as an interface between the user and the server, displaying information and suggestions from the server to the user. Users can receive suggestions from the server by entering specific research topics or questions through the terminal. Educational materials designed for users are provided on the terminal to support the development of new users' expertise. These educational materials include quizzes to deepen basic knowledge and understanding of related fields.

[0633] For example, if a junior chemistry researcher enters the prompt message, "I want to know the latest trends in synthesis methods for new materials," the server generates summaries of relevant literature and proposed experimental designs, which are then displayed on the terminal. In this way, the entire system operates in an integrated manner, streamlining the research and development process and promoting the improvement of the user's knowledge.

[0634] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0635] Step 1:

[0636] The server connects to multiple information sources on the internet and collects research data using APIs. Specifically, the server searches for information sources using specified keywords and stores the retrieved data in a database on the server. The input is the specified keywords and search conditions, and the output is the research data retrieved from the information sources.

[0637] Step 2:

[0638] The server analyzes the collected research data using natural language processing techniques. The server extracts important information and trends from the data using text analysis methods. This process utilizes a generative AI model to generate summaries of relevant papers and articles. The input is the collected research data, and the output is the extracted information and summaries.

[0639] Step 3:

[0640] The terminal displays the analysis results provided by the server to the user. The user can input any prompt text through the terminal, and based on that, will receive suitable suggestions from the server. For example, if a prompt text such as "Please tell me the synthesis method for the new material" is entered, the server will provide information based on the analysis results. The input is the prompt text from the user, and the output is suggestions or information based on the analysis results.

[0641] Step 4:

[0642] The device provides users with educational materials to enhance their expertise. The device displays learning content, including foundational knowledge and quizzes tailored to the user's experience and knowledge level. Input is the user's profile and knowledge level, while output is appropriately customized educational material.

[0643] Step 5:

[0644] The server notifies expert users of the latest research findings and technological trends. Expert users receive these notifications at all times via their terminals and can check detailed information as needed. Inputs are the latest analysis results and the user's areas of interest, and outputs are notifications to expert users.

[0645] Step 6:

[0646] The terminal records the user's operation history and thought process, and sends this data to a server. The server analyzes this data and stores it in the organization's database. The input is the user's operation history and reactions, and the output is the analyzed insights and accumulated knowledge data.

[0647] (Application Example 1)

[0648] 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".

[0649] In modern manufacturing, rapidly changing technological information and the frequent introduction of new materials necessitate the optimization of manufacturing processes. However, information acquisition and analysis are often done manually, leading to challenges such as delays in efficient process improvement and decision-making. Furthermore, training new employees is time-consuming and costly, making it difficult to cultivate them into immediately productive members of the workforce. A system is needed to solve these problems and maximize the efficiency of manufacturing processes.

[0650] 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.

[0651] In this invention, the server includes means for collecting research information, means for analyzing the collected research information using natural language processing technology, and means for collecting technical information for improving efficiency in the manufacturing process and optimizing its operation based on that information. This enables the immediate incorporation of the latest technologies into the manufacturing line and rapid and effective process optimization. Furthermore, it is possible to improve the overall technical knowledge of the organization by providing learning materials to support the improvement of expertise for new employees and notifying expert users of the latest research results and technological trends.

[0652] "Research information" refers to knowledge obtained from scientific and technological papers, articles, and databases.

[0653] "Natural language processing technology" is an artificial intelligence technology that analyzes text data and extracts important information.

[0654] A "manufacturing process" is a set of steps and procedures necessary to complete a product.

[0655] "Efficiency optimization" is an optimization process aimed at achieving maximum results while minimizing resources and time.

[0656] "Technical information" refers to the latest knowledge regarding new technologies, methods, and materials.

[0657] "Optimizing operation" means making adjustments to maximize the performance of a system, machine, or process.

[0658] A "new user" refers to a user who has recently joined a particular field or organization.

[0659] "Learning materials that support the improvement of expertise" refer to educational materials provided to help acquire specific skills or specialized knowledge.

[0660] An "expert user" refers to a user who possesses advanced knowledge and experience in a specific field.

[0661] "Latest research findings and technological trends" refer to information that indicates the newest discoveries and directions of development in current science and technology.

[0662] "Accumulating knowledge" means organizing experiences and information and saving them in a way that can be used in the future.

[0663] The server collects research information and performs analysis using natural language processing technology. It accesses databases and technical article sites on the internet via APIs to obtain the latest technical information. The retrieved information is stored in a database, and important information and technological trends are extracted using natural language processing. This allows users to quickly obtain the information necessary to improve the efficiency of their manufacturing processes.

[0664] The terminal functions as an interface with the user. Through the terminal, users can receive research procedures and suggestions for the latest technologies. The terminal also provides learning materials to help new users improve their expertise, supporting their learning through quiz-based training and summaries of relevant literature. Expert users are notified of the latest research results and technological trends analyzed by the server, helping them optimize manufacturing processes efficiently and effectively.

[0665] This system allows users to share technical insights and thought processes, strengthening the knowledge base across the entire organization. This data will be used for future projects and training new employees.

[0666] For example, if a manufacturing plant plans to introduce a new material, the server collects and analyzes relevant technical information and provides the user with optimal manufacturing procedures and improvement suggestions via a terminal. This allows the plant to quickly begin manufacturing using the properties of the new material.

[0667] An example of a prompt to input into a generative AI model is: "Suggest ways to improve the efficiency of a manufacturing line using AI. How will you collect and analyze information on the latest manufacturing technologies and materials?"

[0668] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0669] Step 1:

[0670] The server accesses databases and article sites on the internet via APIs to retrieve the latest research information. The input consists of URLs of the information sources to be collected and query conditions, while the output includes the retrieved text data. This data is then prepared within the server for the following processing.

[0671] Step 2:

[0672] The server performs analysis on the acquired text data using natural language processing techniques. The input is the text data acquired in the previous step, and the output extracts important information and technology trends. Specific operations include text tokenization, keyword extraction, and topic modeling.

[0673] Step 3:

[0674] The server generates technical information for efficiency improvements based on the analysis results and sends it to the terminal. The inputs used are extracted key information and technology trends, while the output includes optimization suggestions and improvement measures. This operation enables the provision of concrete suggestions to the user.

[0675] Step 4:

[0676] The terminal displays suggested technical information and improvement measures so that the user can view them through the interface. The input is technical information sent from the server, and the output is presented as visual information that the user can view on the screen. Based on this, the user obtains guidance for improving the manufacturing process.

[0677] Step 5:

[0678] Users improve their expertise through quizzes and literature summaries using learning materials provided on their devices. Input includes specific learning themes and fields, and output aims to improve the user's knowledge. Specific actions include interactive quizzes and the display of relevant literature summaries.

[0679] Step 6:

[0680] Expert users receive notifications of the latest research findings and technological trends analyzed by the server via their terminals. The input is the latest analysis results, and the output includes information in the form of notifications. This process allows users to quickly obtain the information necessary to improve their manufacturing processes.

[0681] Step 7:

[0682] The server records user actions and thought processes, and stores the obtained data in the organization's database. Inputs include user behavior data and feedback, while outputs include accumulated knowledge data. Through this process, the knowledge base of the entire organization is strengthened.

[0683] 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.

[0684] This invention is implemented in a form that combines a system for streamlining the research and development process with an emotion engine that recognizes user emotions. This system consists of a server, a terminal, and an emotion engine.

[0685] The server accesses scientific databases and technology article sites on the internet, collecting research information via APIs. The server analyzes this information using natural language processing techniques to identify important technology trends. This enables the efficient collection and analysis of information necessary for research.

[0686] The terminal acts as the interface with the user, receiving research topics and questions from the user. Based on information sent from the server and the analysis results from the emotion engine, the terminal proposes an optimized research process for the user. The emotion engine analyzes the user's facial expressions and voice input to determine their emotional state, and uses that data to personalize the user's experience.

[0687] As a concrete example, when a new user uses a terminal to learn about a new experimental technique, the server collects relevant information and proposes an experimental process based on it. At the same time, an emotion engine monitors the user's emotional state and adjusts the content to provide slower, more detailed explanations if the user is feeling anxious or stressed. This allows new users to efficiently improve their expertise while reducing stress.

[0688] Furthermore, for expert users, the system helps them stay up-to-date by promptly notifying them of the latest research results and technological trends. The emotion engine also detects the emotional state of the expert user's work environment and suggests relaxation methods if emotions that hinder concentration arise. In this way, the present invention is a multi-functional support system that enables researchers to conduct their research efficiently in an optimal environment.

[0689] The following describes the processing flow.

[0690] Step 1:

[0691] The server accesses scientific databases and technical article sites on the internet and retrieves the necessary research information via APIs. The retrieved data is then filtered based on specific keywords.

[0692] Step 2:

[0693] The server analyzes research information acquired using natural language processing techniques. Topic modeling is utilized to extract important technology trends and keywords from the data.

[0694] Step 3:

[0695] The terminal provides an interface for receiving research topics and questions from users. Users input questions and interests related to their own research into the terminal.

[0696] Step 4:

[0697] The emotion engine analyzes the user's facial expressions and voice to identify their emotional state at that moment. The emotion engine provides information such as whether the user is stressed or calm.

[0698] Step 5:

[0699] The server integrates user input information with data from the emotion engine and uses an AI model to propose a research process. This proposal includes experimental design and training content. This proposal is then sent to the user via the device.

[0700] Step 6:

[0701] The device provides learning materials tailored to the emotional state of new users. If a user is feeling anxious, it provides detailed explanations and materials with an adjusted pace.

[0702] Step 7:

[0703] The server notifies expert users of the latest research findings and technology trends on their devices. An emotion engine monitors the expert's emotional state and provides feedback to help them maintain focus.

[0704] Step 8:

[0705] The system records user operation logs and emotional state data on the terminal and sends them to the server. The server uses this data to update the organization's knowledge database and utilize it for future research and education.

[0706] (Example 2)

[0707] 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".

[0708] Traditional research support systems require the collection and analysis of large amounts of data, but lack adaptive support tailored to the user's emotional state. Furthermore, when novice and expert users receive the same information, the depth and speed of that information are often inappropriate. In addition, the lack of a mechanism for systematically accumulating and utilizing collected knowledge hinders efficient research activities.

[0709] 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.

[0710] In this invention, the server includes means for collecting research information, means for analyzing the information using analytical techniques, and means for proposing a research process to the user based on the analysis results. This makes it possible to provide information optimized by expertise while taking into account the user's emotional state. Furthermore, it realizes a system that enables efficient accumulation and sharing of knowledge within the organization.

[0711] "Research information" refers to information such as data, literature, and articles related to scientific investigations and technical analyses.

[0712] "Analytical techniques" refer to a set of methods and technologies for processing collected data and extracting meaningful information and trends.

[0713] "Users" refer to individuals with diverse knowledge levels, such as experts and newcomers, who use the system for research activities.

[0714] "Emotional state" refers to the psychological condition exhibited by the user, and includes emotions detected from facial expressions, voice, etc.

[0715] "Educational materials" refer to teaching materials and reference materials provided to support users' learning and improvement of their expertise.

[0716] "Expertise" refers to the state of possessing a high level of knowledge and skills in a particular field.

[0717] A "wide-area communication network" refers to widely used communication networks such as the internet, which provide an environment where diverse information sources can be accessed.

[0718] An "interface" is a technology that refers to the boundary or point of contact used when a user and a system exchange information.

[0719] "Question-and-answer format questions" refers to interactive formats that include quizzes and questions provided to check the user's understanding.

[0720] "Summary of related literature" refers to summary information that extracts important information from multiple sources and provides it in a shortened format.

[0721] This invention is a system aimed at the efficient collection and analysis of research information and the optimization of the user experience based on emotions. The system mainly consists of a server, terminals, and an emotion engine.

[0722] The server accesses diverse data sources on a wide-area communication network and collects research information using interfaces. Specifically, it retrieves information from databases and article databases on the internet. This information is then analyzed using analytical techniques. The server implements natural language processing libraries using Python and Java to break down the collected data into topics and extract important technology trends. This process enables the efficient provision of the technology information that users need.

[0723] The terminal is responsible for the user interface. When the user inputs a research topic or question, this information is sent to the server, and based on the analysis results and the sentiment engine's judgment, personalized suggestions are provided to the user. Frameworks such as React and Angular are used to build the user interface and enhance usability.

[0724] The emotion engine is responsible for detecting the user's emotional state and personalizing the experience. Specifically, it includes a cloud-based speech recognition API for analyzing voice input and image processing technology used for facial expression analysis. This allows for the real-time detection of user anxiety and confusion, enabling the presentation of information and adjustment of the learning pace accordingly.

[0725] For example, if a user uses the system to learn the "fundamentals of quantum computing," the server aggregates and analyzes relevant academic information. The terminal then provides optimal information while considering the user's emotional state. If the user shows signs of impatience, the emotion engine detects this and adjusts the content to make the explanation easier to understand. An example of a prompt in this case would be, "Please provide a concise explanation of the fundamentals of quantum computing. Please also provide more detailed information depending on the user's level of understanding."

[0726] Thus, the present invention is a new form of research support system that enables the provision of information tailored to the diverse needs of users, as well as the accumulation and sharing of knowledge.

[0727] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0728] Step 1:

[0729] The server receives research topics and questions entered by the user. Based on this input, it accesses multiple information sources on a wide-area communication network through the interface and collects relevant research information. Specifically, the server uses keywords to send queries to databases and article areas via APIs and retrieves highly relevant results. The output is a collection of raw data related to the target research topic.

[0730] Step 2:

[0731] The server analyzes collected research information using natural language processing techniques. It parses and tokenizes the raw input data. Furthermore, it utilizes machine learning models to extract topics and perform trend analysis. Specifically, it performs language analysis using Python's natural language processing library and clustering using a generative AI model. The output obtained from this process is a summary of analyzed and classified technology trends and themes.

[0732] Step 3:

[0733] The terminal sends analysis results from the server and emotional state data entered by the user to the emotion engine. The input consists of facial expressions and voice data shown by the user to the terminal, and the emotion engine uses this to determine the emotional state. The operation involves analysis using facial recognition software and emotion estimation using a voice recognition API. The output is evaluation data that quantifies the user's emotional state.

[0734] Step 4:

[0735] The terminal integrates output from the emotion engine with server analysis results to provide a research process and information presentation optimized for the user. The input is integrated data, and its specific actions include visualization and information organization through the user interface. Through this process, the user receives information adjusted according to their level of understanding and emotions.

[0736] Step 5:

[0737] Users advance their research activities based on optimization information provided by the device. Specifically, this includes actions taken using presented prompts and technology trends. The input is information suggestions from the device, and the output obtained by the user is new insights and practical results.

[0738] Step 6:

[0739] The terminal collects user feedback and sends it to the server. Inputs include user ratings and comments, and specific actions include using rating forms and feedback widgets. The server then stores this data back into a database for further improvement and analysis. The output is quantified data of insights and experience that helps improve the system.

[0740] (Application Example 2)

[0741] 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".

[0742] Many brick-and-mortar stores face the challenge of declining customer satisfaction and purchasing intent due to insufficient personalized product recommendations and information provision for each individual customer. Furthermore, in fields requiring specialized knowledge, the collection and analysis of research information is time-consuming, necessitating more efficient processes.

[0743] 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.

[0744] In this invention, the server includes means for collecting research information, means for analyzing the collected research information using natural language processing technology, and means for recognizing the customer's emotional state and providing a personalized in-store experience. This enables product suggestions tailored to the customer's emotions, provides researchers with efficient information collection and analysis, and improves satisfaction for both parties.

[0745] "Means of collecting research information" refers to the general term for methods and equipment used to access scientific databases and technical article websites and obtain necessary information.

[0746] "Natural language processing technology" refers to a series of technologies that enable computers to understand human language and analyze its meaning.

[0747] "Means of proposing research processes" refers to methods of showing users how to conduct research efficiently based on the information collected.

[0748] "Means of providing learning materials" refers to methods of preparing materials to assist new users in acquiring knowledge and skills.

[0749] A "means of notifying users of the latest research results and technological trends" refers to a system that keeps users informed so they can always access new information.

[0750] "Means for recording knowledge and thought processes" refers to methods for saving users' technical knowledge and ideas and making them shareable within an organization.

[0751] "Means of recognizing emotional states" refers to technologies that analyze a customer's facial expressions and voice to understand their current psychological state.

[0752] "Means of providing personalized experiences" refers to methods for tailoring and delivering information and services precisely according to the individual needs and emotions of each customer.

[0753] "Methods for making product recommendations" refer to techniques for recommending appropriate products based on the customer's interests and feelings.

[0754] This system consists of a server, a user terminal, and an emotion recognition engine. The server accesses databases and article sites on the internet and retrieves research information using APIs. This information is analyzed using natural language processing techniques to extract specific trends and necessary content. The server also utilizes generative AI models to generate personalized suggestions tailored to the user's emotional state.

[0755] User terminals are devices such as smartphones and tablets used in stores, and they analyze customer emotions through facial recognition and voice input. For this purpose, the terminals are equipped with cameras and microphones, and open-source facial recognition libraries and voice recognition engines are installed.

[0756] Based on the emotional data the system has gathered, it proposes the most suitable products and services to customers. Specifically, it inputs prompts such as, "Customer appears unsure. Generate a friendly guide to assist in choosing the perfect product based on their preferences and previous shopping history," into the generating AI model, which then generates appropriate guidance.

[0757] For example, if a customer finds an item they're interested in in the store but wants more detailed information, this system can quickly provide rich content and details. In this way, it can improve customer satisfaction and purchasing intent while also reducing the workload on staff.

[0758] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0759] Step 1:

[0760] The server accesses databases and article sites on the internet. It uses APIs to retrieve research information. The input is a search query based on the user's research topic and interests, and the output is a list of specific information. This information serves as raw material for subsequent natural language processing.

[0761] Step 2:

[0762] The server uses natural language processing techniques on the acquired information list to extract technology trends and useful information. In this process, a text analysis algorithm analyzes the input data to extract keywords and identify trends. The output is an abstracted set of information resulting from the analysis.

[0763] Step 3:

[0764] The device uses a camera and microphone to collect facial expressions and audio data of customers in the store. The input is specific visual and audio data, and the output is the result of an emotional state evaluation by an emotion recognition engine. This evaluation result is used to make personalized suggestions in the next step.

[0765] Step 4:

[0766] The server inputs prompt sentences generated based on emotional states and research information into the generating AI model. Specifically, it generates prompt sentences such as, "Customer appears unsure. Generate a friendly guide to assist in choosing the perfect product based on their preferences and previous shopping history," and instructs the AI. The output is guidance and suggestions tailored to the customer's needs.

[0767] Step 5:

[0768] The user terminal receives responses from the AI ​​and presents them to the customer. The input is the AI's suggestions, and the output is information provided through the user interface. Specifically, this includes on-screen recommendations and voice guidance. In this step, the customer's purchasing decision is supported by viewing and listening to the suggestions.

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

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

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

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

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

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

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

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

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

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

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

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

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

[0782] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

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

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

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

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

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

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

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

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

[0791] (Claim 1)

[0792] Means of collecting research information,

[0793] A means of analyzing collected research information using natural language processing technology,

[0794] A means of proposing a research process to the user based on the analyzed results,

[0795] A means of providing learning materials to support the improvement of expertise for new users,

[0796] A means of notifying expert users of the latest research results and technological trends,

[0797] A means of recording users' technical knowledge and thought processes, and accumulating knowledge within the organization,

[0798] A system that includes this.

[0799] (Claim 2)

[0800] The system according to claim 1, which includes means for accessing databases and article sites on the internet and obtaining information using APIs in the collection of research information.

[0801] (Claim 3)

[0802] The system according to claim 1, comprising means for providing learning materials that support the improvement of expertise, such as quizzes and summaries of relevant literature to aid the user's understanding.

[0803] "Example 1"

[0804] (Claim 1)

[0805] A device for collecting research data,

[0806] A device that analyzes collected research data using natural language processing technology,

[0807] A device that extracts important information and trends from data analyzed using a generative AI model,

[0808] A device that proposes research methods to the user based on extracted information,

[0809] A device that provides educational materials to help new users improve their expertise,

[0810] A device that supports user understanding by including basic knowledge and quizzes in related fields in educational materials,

[0811] A device that notifies expert users of the latest research results and technological trends,

[0812] A device that records user operation history and thought processes to accumulate knowledge within the organization,

[0813] A system that includes this.

[0814] (Claim 2)

[0815] The system according to claim 1, comprising a device that accesses information sources on the internet and obtains research data using an API.

[0816] (Claim 3)

[0817] The system according to claim 1, comprising a device that provides educational materials with quizzes and summaries of related materials to deepen the user's knowledge.

[0818] "Application Example 1"

[0819] (Claim 1)

[0820] Means of collecting research information,

[0821] A means of analyzing collected research information using natural language processing technology,

[0822] A means of suggesting research procedures to the user based on the analyzed results,

[0823] A means of providing learning materials to support the improvement of expertise for new users,

[0824] A means of notifying expert users of the latest research results and technological trends,

[0825] A means of recording users' technical knowledge and thought processes, and accumulating knowledge within the organization,

[0826] A means for collecting technical information to improve efficiency in the manufacturing process and optimizing operations based on that information,

[0827] A system that includes this.

[0828] (Claim 2)

[0829] The system according to claim 1, which includes means for accessing databases and article sites on the internet and obtaining information using APIs in the collection of research information.

[0830] (Claim 3)

[0831] The system according to claim 1, comprising means for providing learning materials that support the improvement of expertise, such as quizzes and summaries of relevant literature to aid the user's understanding.

[0832] "Example 2 of combining an emotion engine"

[0833] (Claim 1)

[0834] Means of collecting research information,

[0835] A means of analyzing collected research information using analytical techniques,

[0836] A means of suggesting a research process to the user based on the analyzed results,

[0837] A means of providing educational materials to support the improvement of expertise among new users,

[0838] A means of notifying expert users of the latest research results and technological trends,

[0839] A means of detecting the user's emotional state and personalizing the learning experience,

[0840] A means of recording users' technical knowledge and thought processes, and accumulating knowledge within the organization,

[0841] A system that includes this.

[0842] (Claim 2)

[0843] The system according to claim 1, which includes means for accessing databases and article areas on a wide-area communication network and obtaining information using an interface in the collection of research information.

[0844] (Claim 3)

[0845] The system according to claim 1, comprising means for providing educational materials with question-and-answer format questions and summaries of relevant literature to aid user understanding.

[0846] "Application example 2 of combining emotional engines"

[0847] (Claim 1)

[0848] Means of collecting research information,

[0849] A means of analyzing collected research information using natural language processing technology,

[0850] A means of proposing a research process to the user based on the analyzed results,

[0851] A means of providing learning materials to support the improvement of expertise for new users,

[0852] A means of notifying expert users of the latest research results and technological trends,

[0853] A means of recording users' technical knowledge and thought processes, and accumulating knowledge within the organization,

[0854] A means of recognizing the customer's emotional state and providing a personalized in-store experience,

[0855] A means of making product suggestions to customers that respond to their emotions,

[0856] A system that includes this.

[0857] (Claim 2)

[0858] The system according to claim 1, which includes means for accessing databases and article sites on the internet and obtaining information using APIs in the collection of research information.

[0859] (Claim 3)

[0860] The system according to claim 1, comprising means for providing learning materials that support the improvement of expertise, such as quizzes and summaries of relevant literature to aid the user's understanding. [Explanation of Symbols]

[0861] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. Means of collecting research information, A means of analyzing collected research information using natural language processing technology, A means of proposing a research process to the user based on the analyzed results, A means of providing learning materials to support the improvement of expertise for new users, A means of notifying expert users of the latest research results and technological trends, A means of recording users' technical knowledge and thought processes, and accumulating knowledge within the organization, A system that includes this.

2. The system according to claim 1, which includes means for accessing databases and article sites on the internet and obtaining information using APIs in the collection of research information.

3. The system according to claim 1, comprising means for providing learning materials that support the improvement of expertise, such as quizzes and summaries of related literature to aid the user's understanding.

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