system

Abstract

We provide the system. [Solution] Means of collecting software information from open-source platforms, A means for analyzing the source code of the software information and generating summary data, Means for storing the summary data in a database, A method for extracting relevant keywords from social issues entered by users, A means of searching a database using the keyword and suggesting related software ideas, A means of providing the user with a summary of the proposed software idea and its implementation method, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, including the 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] Society faces various problems, and innovative ideas are required to solve them. However, in a busy environment, it takes a lot of time and effort for many people to come up with effective ideas on their own and implement those ideas as specific services. In the field of open source, although many engineers are developing useful software, there is a high possibility that promising ideas that are not known to the public are buried in it. However, it is very difficult to find relevant ideas by oneself from a huge number of repositories. The purpose of this invention is to solve such problems.

Means for Solving the Problems

[0005] This invention provides a system for collecting software information from open-source platforms, analyzing its source code to generate summary data, and storing this data in a database. Furthermore, it includes a means for extracting relevant keywords when a user inputs a social issue they wish to solve, searching the database based on these keywords, and suggesting relevant software ideas, thereby supporting rapid and efficient problem-solving. In addition, it provides the user with a summary of the proposed software ideas and their implementation methods, enabling the user to obtain the information necessary for implementing specific services.

[0006] An "open-source platform" is a shared infrastructure for software development where the source code of the software is publicly available and can be used, modified, and distributed free of charge.

[0007] "Software information" refers to metadata and source code itself related to a software project, and includes information such as functionality, technologies used, and developer information.

[0008] "Source code" refers to text data written in a programming language that determines how software operates.

[0009] "Summary data" refers to information that concisely expresses important features and functions based on analysis of source code and software information.

[0010] A "database" is a collection of information that systematically stores collected summary data and is organized in a way that facilitates searching and analysis.

[0011] A "keyword" is an important word or phrase identified in relation to a social issue that the user wants to solve.

[0012] A "software idea" is a creative concept for achieving a specific purpose or function using software.

[0013] "Implementation method" refers to the procedures and techniques for transforming a software idea into a form that exhibits concrete functionality. [Brief explanation of the drawing]

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

Embodiments for Carrying Out the Invention

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

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

[0017] In the following embodiments, 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.

[0018] 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.

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

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

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

[0022] [First Embodiment]

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

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

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

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

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

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

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

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

[0031] As shown in Figure 2, in the data processing device 12, 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.

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

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

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

[0035] This invention provides a system for effectively proposing software ideas and implementation methods to solve specific social problems. This system is built on a server and accessible to users via terminals. The main components of the system are a data collection module, a code analysis module, a database module, and a search and proposal module.

[0036] The server uses APIs from open-source platforms to collect daily update information. This process is automated in the backend, and the server periodically retrieves new repository information and saves it to storage. The retrieved information includes the repository name, description, technologies used, and source code.

[0037] Next, the server analyzes the collected source code using a generating AI via a code analysis module. This process summarizes the key functions and technologies of the source code and systematically stores this summary data in a database. This stored summary data is then used in subsequent search and suggestion processes.

[0038] The user uses a terminal to input the social problem they want to solve into the system. The terminal receives the user input, extracts relevant keywords, and sends them to the server. Based on these keywords, the server searches its database for highly relevant software ideas and implementation methods.

[0039] Ultimately, the server presents solutions to the user based on the search results. The terminal visually displays this information to the user, allowing them to evaluate the presented ideas and utilize them for concrete implementation.

[0040] For example, if a user enters a challenge related to "optimizing renewable energy," the system will search its database for relevant projects and suggest repositories that provide optimization algorithms useful for energy management. With this information, the user can then efficiently develop a new energy management system by leveraging the code.

[0041] Thus, the present invention is an effective system that provides users with a means to efficiently solve social problems.

[0042] The following describes the processing flow.

[0043] Step 1:

[0044] The server uses APIs from open-source platforms to collect repository information. This information includes basic metadata, source code, and project descriptions for the repository. Collection is performed regularly to ensure the system has fresh data.

[0045] Step 2:

[0046] The server uses a generative AI model to analyze the retrieved source code. This analysis summarizes the functionality and technology stack used in each repository. The summarized data is concise yet contains important functional elements.

[0047] Step 3:

[0048] The server stores the generated summary data in a database. This database is structured to allow for quick access to user search queries, enabling efficient searching and recommendations.

[0049] Step 4:

[0050] Users input the social issues they want to solve through their device. The device analyzes the input text, extracts relevant keywords, and sends them to the server. The extraction process utilizes natural language processing technology to improve accuracy.

[0051] Step 5:

[0052] The server searches the database based on the received keywords. It lists relevant software ideas and generates summaries of their implementation methods. This process employs advanced filtering techniques to improve the accuracy of keyword matching.

[0053] Step 6:

[0054] The terminal displays the suggestions provided by the server to the user. The user can refer to details and implementation outlines of each presented software idea. The visually organized information facilitates user decision-making.

[0055] Step 7:

[0056] Users select from the presented proposals and download or implement their desired software project. This allows users to efficiently start developing new services and solutions.

[0057] (Example 1)

[0058] 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."

[0059] There is a need to provide information technology that efficiently solves social problems. However, conventional systems have a problem in that they cannot quickly provide useful solutions because they lack the appropriate collection and analysis of relevant information.

[0060] 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.

[0061] In this invention, the server includes means for collecting information from an information sharing infrastructure, means for analyzing the program description of the information and generating summary information, and means for storing the summary information in a storage device. This makes it possible to quickly search for and propose highly relevant technical solutions based on user requests.

[0062] An "information sharing platform" is a platform that makes information such as software and data publicly available, making it accessible to other systems and users.

[0063] "Information" refers to a set of data with a specific purpose or function, including source code and technical specifications that are collected and analyzed.

[0064] "Program description" refers to the code that describes the operation of software, and is the subject of analysis and summarization.

[0065] "Summary information" refers to an overview of important functions and technologies extracted from the analyzed program description.

[0066] A "storage device" is a storage medium or database that stores collected and analyzed information and summary information, and allows it to be searched and referenced when needed.

[0067] "Operator" refers to an individual or organization that attempts to solve social problems using a system.

[0068] A "social problem" is an issue or challenge that affects the public interest and is something that is attempted to be solved through systems.

[0069] "Words" are keywords or phrases extracted from the operator's input and are used for information retrieval and relevance evaluation.

[0070] A "concept" refers to a proposed software idea or technical method that can be used to solve a problem.

[0071] To implement this invention, the server needs to have a system in place to collect information from an information sharing platform. For this purpose, the server utilizes an API to obtain open-source information via an internet connection. The API used in this case is one provided by a code repository.

[0072] The server utilizes a generative AI model to analyze the collected information. This generative AI model automatically analyzes the provided program description and generates a summary of the information. The generated summary is then stored directly in a storage device. A relational database is used as the storage device. This will enable efficient data retrieval and suggestions in the future.

[0073] The user uses a terminal to input a social problem they want to solve into the system. For example, they might input a problem such as "optimization of renewable energy" and generate a prompt based on that problem. An example of a prompt might be, "Please propose an open-source project that implements an algorithm for optimizing renewable energy."

[0074] The terminal analyzes the input information, extracts relevant terms, and sends them to the server. The server searches for storage devices based on these terms and suggests relevant concepts to the user. The user can then proceed with specific software development or technology application based on the presented information.

[0075] The technologies and methods used throughout this system are designed to allow users to efficiently obtain necessary technical information, even without specific expertise. Therefore, it can play a role in supporting rapid decision-making and implementation in projects that advance information technology-based problem-solving.

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

[0077] Step 1:

[0078] The server collects information from an information sharing platform. The input is an API for code repositories accessible via the internet. The server calls the API to retrieve a list of software repositories. This process collects information such as the repository name, description, technologies used, and source code, and records it in storage.

[0079] Step 2:

[0080] The server analyzes the collected information using a generative AI model. The input is the repository information collected in step 1. The server passes the source code to the generative AI model, which analyzes important functions and technologies to create summary information. The output is the summary information, which is systematically stored in a database.

[0081] Step 3:

[0082] The user uses a terminal to input a social problem they wish to solve into the system. The input is the social issue the user types into the terminal. The terminal extracts relevant keywords from this input and sends them to the server. This process clarifies the user's intent and effectively guides the system's search function.

[0083] Step 4:

[0084] The server searches the database using the received terms. The input is the terms extracted in step 3. The server searches the database for summary information and selects the most relevant software concepts and implementation methods. The output is a set of ideas proposed to the user.

[0085] Step 5:

[0086] The terminal visually displays suggestions sent from the server to the user. The input consists of suggested ideas that the server has searched for and selected. The terminal displays this information on the screen, helping the user evaluate each suggestion and decide how to specifically use it. This step allows the user to make quick decisions based on the information provided.

[0087] (Application Example 1)

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

[0089] With the development of smart cities, many social challenges have become more complex, and solutions are needed. These challenges include optimizing resources, mitigating traffic congestion, and improving energy efficiency. To effectively solve these problems, it is essential to accurately combine various technologies and their implementation methods. However, it is often difficult for users to find appropriate technological ideas and implementation methods on their own due to a lack of knowledge and information. To improve this situation, there is a need to provide a system that automatically suggests appropriate technological ideas to users and supports the efficient resolution of social challenges.

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

[0091] In this invention, the server includes means for acquiring program information from an open-source technology sharing platform, means for analyzing the source code of the program information and generating summary information, and means for storing the summary information in an information management device. This enables users to efficiently acquire appropriate technical ideas and implementation methods for social issues related to urban functions.

[0092] An "open-source technology sharing platform" is a place that provides freely accessible technical information on the internet and shares information useful for the development of various programs and software.

[0093] "Program information" is a general term for information related to the code, technical specifications, and algorithms used in specific software or applications.

[0094] "Source code" refers to code written in a programming language used to implement a specific function, and is a set of commands that govern the operation of software.

[0095] "Summary information" refers to information that extracts important elements from detailed program information or source code and summarizes them concisely.

[0096] An "information management device" is a system or device for systematically storing and managing large amounts of data, and for making it quickly searchable and available when needed.

[0097] "Users" refer to individuals or organizations that use this system to seek technology and information for the purpose of solving specific problems.

[0098] "Issues related to urban functions" refer to all problems that need to be solved in order to improve the quality of life and efficiency in cities, and include traffic flow, efficient energy use, and waste management.

[0099] A "technical idea" refers to a new technical concept or method devised to solve a specific problem.

[0100] "Implementation method" refers to the procedures and processes necessary to incorporate a technical idea into a system or product in a concrete form.

[0101] The system realizing this invention consists of a network-connected server and a terminal operated by the user. The server automatically retrieves program information from an open-source technology sharing platform. This program information includes the source code, technical specifications, and information about the technologies used in the software and applications. The server analyzes the retrieved information using a code analysis module, extracts important elements, and generates summary information. This summary information is stored in an information management device for efficient data management and is later used for searching based on user input.

[0102] The user uses a terminal to input the social challenges they are currently facing. The terminal processes the input, extracts relevant keywords, and sends them to a server. Based on the received keywords, the server searches for information management devices and identifies relevant technological ideas and implementation methods. The server uses a generative AI model to evaluate multiple solutions and presents the best one to the user. Finally, the terminal presents the user with a summary, providing direction toward solving specific social challenges.

[0103] The main hardware consists of server devices for processing information and terminals for operating the user interface, while the software includes software for managing generative AI models and information management devices. Specifically, the server runs analysis programs written in Python, and the generative AI models use models such as GPT-4(registered trademark). For information management, a SQL-based database management system is used to efficiently store and retrieve information.

[0104] For example, if a user inputs a problem such as "How can we optimize urban energy consumption?", the server will search for relevant program information from the information management device and present technical ideas useful for optimizing energy management. An example of a prompt to the generating AI model in this case is as follows: "Problem: Optimizing urban energy consumption Goal: Efficient energy management Search: Energy management optimization algorithm"

[0105] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0106] Step 1:

[0107] The server automatically retrieves program information from open-source technology sharing platforms. During this retrieval process, it periodically collects newly published information using specific APIs and stores it as program data. This information includes the software's source code and technical specifications.

[0108] Step 2:

[0109] The server inputs the acquired program information into a code analysis module and performs the analysis. The analysis utilizes a generative AI model to identify key elements within the program information and generate summary information. At this stage, major functions and technical features are extracted and stored as summary information in the information management device.

[0110] Step 3:

[0111] The user uses a terminal to input the social issue they want to solve as text. The terminal performs basic natural language processing on the input issue to extract relevant keywords, which are then sent to the server.

[0112] Step 4:

[0113] The server uses the received keywords to search the information management device and identify relevant technical ideas and implementation methods. Here, a database search algorithm is used to extract highly relevant information from the summary information, while duplicate removal and importance evaluation of the results are performed in parallel.

[0114] Step 5:

[0115] The server evaluates multiple solutions based on technical ideas obtained using a generative AI model. It scores the options and determines the most appropriate technical idea and its implementation method. It generates prompts and sends them to the AI, and evaluates the responses to formulate the optimal solution.

[0116] Step 6:

[0117] The device presents the user with a summary of the optimal technical idea and implementation method. This summary is presented in a visually easy-to-understand format, serving as clear guidance on the user's next course of action.

[0118] 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.

[0119] This invention provides a system that automatically collects software information from open-source platforms and combines it with an emotion engine to suggest optimal software ideas to the user. The system runs on a server and is accessible to users via a terminal. The system's main components include a data collection module, a code analysis module, a database module, a search and suggestion module, and an emotion engine.

[0120] The server automatically collects repository information from open-source platforms. This is done using APIs, and the information is updated regularly. The collected information includes the project name, description, source code, and related technical information.

[0121] Next, the server analyzes the source code through a code analysis module and generates summary data using a generative AI model. This summary data concisely represents the project's functions and characteristics and is stored in a database. This database is designed to enable efficient searching and suggestions.

[0122] The user inputs a social issue they want to solve through a terminal. The terminal receives and analyzes this input, extracts relevant keywords, and sends them to the server. The server searches its database based on the received keywords and suggests relevant software ideas.

[0123] Furthermore, the emotion engine recognizes the user's emotions and adjusts the suggestions based on this information. For example, the emotion engine detects whether the user is excited or stressed and makes suggestions tailored to that state. This emotion data is stored in a database along with past suggestion history and used to optimize future suggestions.

[0124] Users receive suggested ideas via their devices and review visually organized information. For example, if a user is looking for software related to "improving digital access for seniors," the emotion engine analyzes the user's interests and suggests software and tools that meet this need. This process allows users to receive suggestions optimized for their emotions and needs, enabling them to quickly begin implementing new projects.

[0125] Thus, the present invention provides a unique system that enables users to find more appropriate and effective software solutions based on their emotions.

[0126] The following describes the processing flow.

[0127] Step 1:

[0128] The server automatically collects metadata and source code from each repository using the API of the open-source platform. This collection process is performed periodically to retrieve newly updated information.

[0129] Step 2:

[0130] The server analyzes the collected source code using an AI model. This summarizes the functionality of each repository, the technical resources used, and the characteristics of the project, generating summary data.

[0131] Step 3:

[0132] The server structures and stores the generated summary data in a database. This database is indexed to enable efficient searching and allows queries to be processed quickly.

[0133] Step 4:

[0134] The user uses a device to input the social issue they want to solve in natural language. The device receives this input, uses a text analysis tool to extract relevant keywords, and sends them to the server.

[0135] Step 5:

[0136] The server queries the database based on the received keywords to find relevant software ideas. The search results include summaries of the relevant projects and their implementation methods.

[0137] Step 6:

[0138] The terminal presents the user with results provided by the server. This includes a project overview, technology stack, expected effects, and implementation tips. The user also receives information related to their emotional state as perceived by the emotion engine.

[0139] Step 7:

[0140] The emotion engine analyzes user input and responses to identify the user's emotional state. For example, it determines whether the user is excited or calm based on text and interactions.

[0141] Step 8:

[0142] The server uses emotion data recognized by the emotion engine to refine the software ideas it proposes. Based on the user's emotions, it prioritizes presenting ideas that are more likely to be accepted by the user.

[0143] Step 9:

[0144] The user reviews the refined proposals and selects the software idea they deem best. Based on this, they begin implementing the project. The selected proposal has a mechanism to provide feedback for later improvement.

[0145] (Example 2)

[0146] 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".

[0147] In modern society, while a wide variety of software is being developed, it has become difficult to quickly and appropriately find the necessary software solutions. Furthermore, there is a lack of systems that provide solution suggestions optimized for the user's emotional state, so users often receive suggestions that do not fully meet their needs. This invention aims to solve these problems.

[0148] 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.

[0149] In this invention, the server includes means for collecting program information from an information sharing platform, means for analyzing the instruction set of the program information and generating summary information, and means for storing the summary information in a storage device. This makes it possible to quickly and appropriately propose relevant program designs in response to social issues input by the user and to provide optimal solutions that correspond to the user's emotional state.

[0150] An "information sharing platform" refers to a platform that provides repository information, such as that for open-source projects, and enables the collection of diverse software information.

[0151] "Program information" refers to technical information related to software and applications, including names, descriptions, and instruction sets.

[0152] A "set of instructions" refers to a series of program code written to control the operation of software.

[0153] "Summary information" refers to information that concisely expresses the main features and functions extracted from program information.

[0154] A "storage device" refers to a database system that stores generated summary information and related data, enabling efficient searching and retrieval.

[0155] A "user" refers to a person who inputs social issues and utilizes the service in order to receive software suggestions through the system.

[0156] "Characteristic terms" refer to highly relevant keywords and phrases extracted from the social issues entered by users.

[0157] "Program design" refers to new software ideas or solutions generated based on information obtained from an information sharing platform.

[0158] "Emotion recognition function" refers to technology that analyzes the user's emotional state and adjusts the suggested solutions accordingly.

[0159] This invention is a system that automatically collects program information from an information sharing platform and proposes the most suitable program design to the user by utilizing a generated AI model and emotion recognition function. This system runs as a software application on a general computer server and can be accessed by users from their terminals via a web browser.

[0160] In this system, the server retrieves program information from an information sharing platform (for example, a common open-source platform) using an API. Specific information includes the project name, description, instruction set (source code), and related technical information. To efficiently analyze and store this data, the server uses a database system (for example, a MySQL database) to store the information.

[0161] The server then uses a generative AI model (for example, the "GPT" model) to analyze the acquired set of instructions. It is prompted with the message, "Please briefly summarize the project's objectives and characteristics," and generates a concise summary.

[0162] The user inputs text about a social issue they want to solve using a terminal. The terminal analyzes the user input and extracts key words. These key words are sent to a server, which searches its database and suggests relevant program ideas.

[0163] The emotion recognition function operates on the server, analyzing the user's emotional state from their input and responses. Based on this data, the proposed program design is adjusted to match the user's emotions. For example, if a user is looking for software related to "improving digital access for the elderly," the emotion engine analyzes the user's expectations and proposes software ideas accordingly. In this way, optimal suggestions for the user become possible.

[0164] This system features a unique mechanism for providing more effective and relevant software solutions based on the individual needs and emotions of each user.

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

[0166] Step 1:

[0167] The server collects program information from the information sharing platform. Specifically, it periodically calls repository information using the information sharing platform's API to retrieve program information. It uses API keys and repository URLs as input and obtains program information such as project name, description, and command set as output.

[0168] Step 2:

[0169] The server sends data to a generating AI model to analyze the acquired program information and instruction set. The generating AI model analyzes the instruction set using the prompt statement "Please briefly summarize the project's objectives and characteristics" and generates summary information. The instruction set and prompt statement are used as input, and the generated summary information is obtained as output.

[0170] Step 3:

[0171] The server stores the generated summary information in a storage device. This process utilizes a database system to efficiently organize the information, facilitating subsequent searching and retrieval. The generated summary information is used as input, and the output is a status indicating that saving to the database is complete.

[0172] Step 4:

[0173] The user inputs a social issue they want to solve in text format using a device. The input issue is analyzed by the device, and relevant characteristic words are extracted. The user's text data is used as input, and a list of extracted characteristic words is obtained as output.

[0174] Step 5:

[0175] The server analyzes the list of characteristic words received from the terminal and searches its storage device. It finds relevant program ideas and creates a list of suggestions. The input is a list of characteristic words, and the output is a list of relevant program ideas.

[0176] Step 6:

[0177] The server analyzes the user's emotional state using emotion recognition. Based on this, it adjusts the proposed program design and creates an optimal list of suggestions. The user's input data and response data are used as input, and the adjusted list of suggestions is obtained as output.

[0178] Step 7:

[0179] Users can view visually organized proposals through their devices and see details of software ideas. The input is a list of proposals sent from the server, and the output is feedback tailored to the user's understanding and interests.

[0180] (Application Example 2)

[0181] 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."

[0182] In modern society, there is a need for systems that can analyze individual emotions in real time and provide optimal life support solutions. In particular, for the elderly and in situations with significant emotional fluctuations, the challenge lies in quickly proposing appropriate software and services tailored to the user. However, existing systems lack sufficient accuracy and efficiency in both emotion analysis and software recommendation, and are unable to meet the diverse needs of users.

[0183] 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.

[0184] In this invention, the server includes means for collecting information from an open platform, means for analyzing the data of the software information and generating summary information, and means for analyzing emotions and adjusting the suggested content. This makes it possible to suggest optimal life support resources based on the user's emotional state and individual needs.

[0185] An "open platform" is a publicly accessible collection of information, a space on the internet for providing software and data.

[0186] "Means of collecting information" refers to the methods and techniques for gathering data, and in particular, the process of obtaining useful data from resources on the internet.

[0187] "Means for analyzing data and generating summary information" refers to technologies that analyze acquired data, concisely summarize the necessary information, and generate summary data.

[0188] "Methods for analyzing emotions and adjusting proposals" refers to technologies that analyze the user's emotional response and optimize the proposals provided based on that analysis.

[0189] "Means of proposing life support resources" refer to methods and technologies for presenting software and services that support individuals' daily lives.

[0190] The system of this invention mainly consists of a server, a terminal, and a user. The server is used to automatically collect necessary information from an open platform and analyze the data. A generative AI model is used for the analysis, which generates a summary of the software information and stores it in a database that enables efficient searching.

[0191] The terminal functions as an interface for users to input their challenges. Based on the challenges the user is facing, it extracts relevant keywords and sends them to the server. The server then searches its database based on this keyword information and suggests the most relevant software ideas and implementation methods.

[0192] Furthermore, the server uses an emotion analysis engine to evaluate the user's emotions in real time. This analysis makes it possible to adjust the recommendations based on the user's emotions. For example, if an elderly person feels stressed while preparing dinner, a relaxation music app can be recommended. In this way, the system proposes the most suitable life support resources for the user and provides services that meet the user's needs and emotions.

[0193] The process described above aims to efficiently find useful software and services for users and improve their quality of life. As a concrete example, consider a prompt message: "Simulate a scenario where an elderly person feels stressed while preparing dinner and a relaxation music app is recommended." Based on this information, a system is created that provides the most suitable suggestions to the user.

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

[0195] Step 1:

[0196] The server collects software information from open platforms. It receives data obtained from the platform's APIs as input, analyzes this data, and extracts the name, description, source code, and related technical information for each project. As output, it formats the collected information and prepares it for further processing.

[0197] Step 2:

[0198] The server analyzes the collected source code and generates summary data using a generative AI model. It receives the formatted information from step 1 as input and uses a data analysis algorithm to summarize the project's functions and characteristics. As output, it stores the generated summary data in a database that allows for efficient searching.

[0199] Step 3:

[0200] The user inputs the problem they want to solve via their device. The system receives the problem or issue in text format as input and extracts relevant keywords based on its content. The extracted keywords are then sent to the server as output and used for database searches.

[0201] Step 4:

[0202] The server searches the database using the keywords received in step 3 and suggests relevant software ideas. It receives keywords as input and queries the database to extract highly relevant summary data. As output, it prepares the extracted software ideas for use in the next process.

[0203] Step 5:

[0204] The server uses an emotion analysis engine to evaluate the user's emotions and adjust the suggestions accordingly. It receives user voice and facial expression data as input and uses an emotion analysis algorithm to identify the user's emotional state. As output, it provides evolved software suggestions tailored to that emotional state.

[0205] Step 6:

[0206] The user receives the final proposal via their device and visually confirms the specific implementation methods. The system receives the adjusted proposal as input and displays it in the user interface. As output, it displays the proposal in an easy-to-understand format and presents feasible options.

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

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

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

[0210] [Second Embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0223] This invention provides a system for effectively proposing software ideas and implementation methods to solve specific social problems. This system is built on a server and accessible to users via terminals. The main components of the system are a data collection module, a code analysis module, a database module, and a search and proposal module.

[0224] The server uses APIs from open-source platforms to collect daily update information. This process is automated in the backend, and the server periodically retrieves new repository information and saves it to storage. The retrieved information includes the repository name, description, technologies used, and source code.

[0225] Next, the server analyzes the collected source code using a generating AI via a code analysis module. This process summarizes the key functions and technologies of the source code and systematically stores this summary data in a database. This stored summary data is then used in subsequent search and suggestion processes.

[0226] The user uses a terminal to input the social problem they want to solve into the system. The terminal receives the user input, extracts relevant keywords, and sends them to the server. Based on these keywords, the server searches its database for highly relevant software ideas and implementation methods.

[0227] Ultimately, the server presents solutions to the user based on the search results. The terminal visually displays this information to the user, allowing them to evaluate the presented ideas and utilize them for concrete implementation.

[0228] For example, if a user enters a challenge related to "optimizing renewable energy," the system will search its database for relevant projects and suggest repositories that provide optimization algorithms useful for energy management. With this information, the user can then efficiently develop a new energy management system by leveraging the code.

[0229] Thus, the present invention is an effective system that provides users with a means to efficiently solve social problems.

[0230] The following describes the processing flow.

[0231] Step 1:

[0232] The server uses APIs from open-source platforms to collect repository information. This information includes basic metadata, source code, and project descriptions for the repository. Collection is performed regularly to ensure the system has fresh data.

[0233] Step 2:

[0234] The server uses a generative AI model to analyze the retrieved source code. This analysis summarizes the functionality and technology stack used in each repository. The summarized data is concise yet contains important functional elements.

[0235] Step 3:

[0236] The server stores the generated summary data in a database. This database is structured to allow for quick access to user search queries, enabling efficient searching and recommendations.

[0237] Step 4:

[0238] Users input the social issues they want to solve through their device. The device analyzes the input text, extracts relevant keywords, and sends them to the server. The extraction process utilizes natural language processing technology to improve accuracy.

[0239] Step 5:

[0240] The server searches the database based on the received keywords. It lists relevant software ideas and generates summaries of their implementation methods. This process employs advanced filtering techniques to improve the accuracy of keyword matching.

[0241] Step 6:

[0242] The terminal displays the suggestions provided by the server to the user. The user can refer to details and implementation outlines of each presented software idea. The visually organized information facilitates user decision-making.

[0243] Step 7:

[0244] Users select from the presented proposals and download or implement their desired software project. This allows users to efficiently start developing new services and solutions.

[0245] (Example 1)

[0246] 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."

[0247] There is a need to provide information technology that efficiently solves social problems. However, conventional systems have a problem in that they cannot quickly provide useful solutions because they lack the appropriate collection and analysis of relevant information.

[0248] 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.

[0249] In this invention, the server includes means for collecting information from an information sharing infrastructure, means for analyzing the program description of the information and generating summary information, and means for storing the summary information in a storage device. This makes it possible to quickly search for and propose highly relevant technical solutions based on user requests.

[0250] An "information sharing platform" is a platform that makes information such as software and data publicly available, making it accessible to other systems and users.

[0251] "Information" refers to a set of data with a specific purpose or function, including source code and technical specifications that are collected and analyzed.

[0252] "Program description" refers to the code that describes the operation of software, and is the subject of analysis and summarization.

[0253] "Summary information" refers to an overview of important functions and technologies extracted from the analyzed program description.

[0254] A "storage device" is a storage medium or database that stores collected and analyzed information and summary information, and allows it to be searched and referenced when needed.

[0255] "Operator" refers to an individual or organization that attempts to solve social problems using a system.

[0256] A "social problem" is an issue or challenge that affects the public interest and is something that is attempted to be solved through systems.

[0257] "Words" are keywords or phrases extracted from the operator's input and are used for information retrieval and relevance evaluation.

[0258] A "concept" refers to a proposed software idea or technical method that can be used to solve a problem.

[0259] To implement this invention, the server needs to have a system in place to collect information from an information sharing platform. For this purpose, the server utilizes an API to obtain open-source information via an internet connection. The API used in this case is one provided by a code repository.

[0260] The server utilizes a generative AI model to analyze the collected information. This generative AI model automatically analyzes the provided program description and generates a summary of the information. The generated summary is then stored directly in a storage device. A relational database is used as the storage device. This will enable efficient data retrieval and suggestions in the future.

[0261] The user uses a terminal to input a social problem they want to solve into the system. For example, they might input a problem such as "optimization of renewable energy" and generate a prompt based on that problem. An example of a prompt might be, "Please propose an open-source project that implements an algorithm for optimizing renewable energy."

[0262] The terminal analyzes the input information, extracts relevant terms, and sends them to the server. The server searches for storage devices based on these terms and suggests relevant concepts to the user. The user can then proceed with specific software development or technology application based on the presented information.

[0263] The technologies and methods used throughout this system are designed to allow users to efficiently obtain necessary technical information, even without specific expertise. Therefore, it can play a role in supporting rapid decision-making and implementation in projects that advance information technology-based problem-solving.

[0264] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0265] Step 1:

[0266] The server collects information from an information sharing platform. The input is an API for code repositories accessible via the internet. The server calls the API to retrieve a list of software repositories. This process collects information such as the repository name, description, technologies used, and source code, and records it in storage.

[0267] Step 2:

[0268] The server analyzes the collected information using a generative AI model. The input is the repository information collected in step 1. The server passes the source code to the generative AI model, which analyzes important functions and technologies to create summary information. The output is the summary information, which is systematically stored in a database.

[0269] Step 3:

[0270] The user uses a terminal to input a social problem they wish to solve into the system. The input is the social issue the user types into the terminal. The terminal extracts relevant keywords from this input and sends them to the server. This process clarifies the user's intent and effectively guides the system's search function.

[0271] Step 4:

[0272] The server searches the database using the received terms. The input is the terms extracted in step 3. The server searches the database for summary information and selects the most relevant software concepts and implementation methods. The output is a set of ideas proposed to the user.

[0273] Step 5:

[0274] The terminal visually displays suggestions sent from the server to the user. The input consists of suggested ideas that the server has searched for and selected. The terminal displays this information on the screen, helping the user evaluate each suggestion and decide how to specifically use it. This step allows the user to make quick decisions based on the information provided.

[0275] (Application Example 1)

[0276] 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."

[0277] With the development of smart cities, many social challenges have become more complex, and solutions are needed. These challenges include optimizing resources, mitigating traffic congestion, and improving energy efficiency. To effectively solve these problems, it is essential to accurately combine various technologies and their implementation methods. However, it is often difficult for users to find appropriate technological ideas and implementation methods on their own due to a lack of knowledge and information. To improve this situation, there is a need to provide a system that automatically suggests appropriate technological ideas to users and supports the efficient resolution of social challenges.

[0278] 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.

[0279] In this invention, the server includes means for acquiring program information from an open-source technology sharing platform, means for analyzing the source code of the program information and generating summary information, and means for storing the summary information in an information management device. This enables users to efficiently acquire appropriate technical ideas and implementation methods for social issues related to urban functions.

[0280] An "open-source technology sharing platform" is a place that provides freely accessible technical information on the internet and shares information useful for the development of various programs and software.

[0281] "Program information" is a general term for information related to the code, technical specifications, and algorithms used in specific software or applications.

[0282] "Source code" refers to code written in a programming language used to implement a specific function, and is a set of commands that govern the operation of software.

[0283] "Summary information" refers to information that extracts important elements from detailed program information and source code and summarizes them concisely.

[0284] "Information management device" refers to a system or device for systematically storing and managing a large amount of data and making it quickly searchable and available when needed.

[0285] "User" refers to people or groups who use this system and seek technology and information for the purpose of solving specific problems.

[0286] "Problems related to urban functions" refer to all problems that are desired to be solved for improving the quality of life and efficiency in cities, including traffic flow, efficient use of energy, waste management, etc.

[0287] "Technical idea" refers to a new technical concept or method devised to solve a specific problem.

[0288] "Implementation method" refers to the procedures and processes necessary to incorporate a technical idea into a system or product in a specific form.

[0289] The system for realizing this invention consists of a network-connected server and a terminal operated by a user. The server automatically acquires program information from an open-source technology sharing platform. The program information includes source code of software and applications, technical specifications, and information on used technologies. The server analyzes the acquired information with a code analysis module, extracts important elements, and generates summary information. This summary information is stored in an information management device for efficient data management and later used for searching based on user input.

[0290] The user uses a terminal to input the social challenges they are currently facing. The terminal processes the input, extracts relevant keywords, and sends them to a server. Based on the received keywords, the server searches for information management devices and identifies relevant technological ideas and implementation methods. The server uses a generative AI model to evaluate multiple solutions and presents the best one to the user. Finally, the terminal presents the user with a summary, providing direction toward solving specific social challenges.

[0291] The main hardware consists of server devices for processing information and terminals for operating the user interface, while the software includes software for managing generative AI models and information management devices. Specifically, the server runs analysis programs written in Python, and the generative AI models use models such as GPT-4. For information management, a SQL-based database management system is used to efficiently store and retrieve information.

[0292] For example, if a user inputs a problem such as "How can we optimize urban energy consumption?", the server will search for relevant program information from the information management device and present technical ideas useful for optimizing energy management. An example of a prompt to the generating AI model in this case is as follows: "Problem: Optimizing urban energy consumption Goal: Efficient energy management Search: Energy management optimization algorithm"

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

[0294] Step 1:

[0295] The server automatically retrieves program information from open-source technology sharing platforms. During this retrieval process, it periodically collects newly published information using specific APIs and stores it as program data. This information includes the software's source code and technical specifications.

[0296] Step 2:

[0297] The server inputs the acquired program information into a code analysis module and performs the analysis. The analysis utilizes a generative AI model to identify key elements within the program information and generate summary information. At this stage, major functions and technical features are extracted and stored as summary information in the information management device.

[0298] Step 3:

[0299] The user uses a terminal to input the social issue they want to solve as text. The terminal performs basic natural language processing on the input issue to extract relevant keywords, which are then sent to the server.

[0300] Step 4:

[0301] The server uses the received keywords to search the information management device and identify relevant technical ideas and implementation methods. Here, a database search algorithm is used to extract highly relevant information from the summary information, while duplicate removal and importance evaluation of the results are performed in parallel.

[0302] Step 5:

[0303] The server evaluates multiple solutions based on technical ideas obtained using a generative AI model. It scores the options and determines the most appropriate technical idea and its implementation method. It generates prompts and sends them to the AI, and evaluates the responses to formulate the optimal solution.

[0304] Step 6:

[0305] The device presents the user with a summary of the optimal technical idea and implementation method. This summary is presented in a visually easy-to-understand format, serving as clear guidance on the user's next course of action.

[0306] Furthermore, an emotion engine for estimating the user's emotion may be combined. That is, the specific processing unit 290 may estimate the user's emotion using the emotion specific model 59 and perform specific processing using the user's emotion.

[0307] The present invention provides a system that automatically collects software information from an open source platform and proposes optimal software ideas for users by combining an emotion engine. This system is executed on a server and can be accessed by users via a terminal. The main components of the system include a data collection module, a code analysis module, a database module, a search and proposal module, and an emotion engine.

[0308] The server automatically collects repository information from the open source platform. This is implemented using an API and the information is updated regularly. The information collected includes the name of the project, description, source code, and related technical information.

[0309] Next, the server analyzes the source code through the code analysis module and generates summary data using the generated AI model. This summary data concisely represents the functions and characteristics of the project and is stored in the database. This database is designed to enable efficient search and proposal.

[0310] The user inputs the social issue to be solved through the terminal. The terminal receives and analyzes this input, extracts relevant keywords, and sends them to the server. The server searches the database based on the received keywords and proposes relevant software ideas.

[0311] Furthermore, the emotion engine recognizes the user's emotions and adjusts the suggestions based on this information. For example, the emotion engine detects whether the user is excited or stressed and makes suggestions tailored to that state. This emotion data is stored in a database along with past suggestion history and used to optimize future suggestions.

[0312] Users receive suggested ideas via their devices and review visually organized information. For example, if a user is looking for software related to "improving digital access for seniors," the emotion engine analyzes the user's interests and suggests software and tools that meet this need. This process allows users to receive suggestions optimized for their emotions and needs, enabling them to quickly begin implementing new projects.

[0313] Thus, the present invention provides a unique system that enables users to find more appropriate and effective software solutions based on their emotions.

[0314] The following describes the processing flow.

[0315] Step 1:

[0316] The server automatically collects metadata and source code from each repository using the API of the open-source platform. This collection process is performed periodically to retrieve newly updated information.

[0317] Step 2:

[0318] The server analyzes the collected source code using an AI model. This summarizes the functionality of each repository, the technical resources used, and the characteristics of the project, generating summary data.

[0319] Step 3:

[0320] The server structures and stores the generated summary data in a database. This database is indexed to enable efficient searching and allows queries to be processed quickly.

[0321] Step 4:

[0322] The user uses a device to input the social issue they want to solve in natural language. The device receives this input, uses a text analysis tool to extract relevant keywords, and sends them to the server.

[0323] Step 5:

[0324] The server queries the database based on the received keywords to find relevant software ideas. The search results include summaries of the relevant projects and their implementation methods.

[0325] Step 6:

[0326] The terminal presents the user with results provided by the server. This includes a project overview, technology stack, expected effects, and implementation tips. The user also receives information related to their emotional state as perceived by the emotion engine.

[0327] Step 7:

[0328] The emotion engine analyzes user input and responses to identify the user's emotional state. For example, it determines whether the user is excited or calm based on text and interactions.

[0329] Step 8:

[0330] The server uses emotion data recognized by the emotion engine to refine the software ideas it proposes. Based on the user's emotions, it prioritizes presenting ideas that are more likely to be accepted by the user.

[0331] Step 9:

[0332] The user reviews the refined proposals and selects the software idea they deem best. Based on this, they begin implementing the project. The selected proposal has a mechanism to provide feedback for later improvement.

[0333] (Example 2)

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

[0335] In modern society, while a wide variety of software is being developed, it has become difficult to quickly and appropriately find the necessary software solutions. Furthermore, there is a lack of systems that provide solution suggestions optimized for the user's emotional state, so users often receive suggestions that do not fully meet their needs. This invention aims to solve these problems.

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

[0337] In this invention, the server includes means for collecting program information from an information sharing platform, means for analyzing the instruction set of the program information and generating summary information, and means for storing the summary information in a storage device. This makes it possible to quickly and appropriately propose relevant program designs in response to social issues input by the user and to provide optimal solutions that correspond to the user's emotional state.

[0338] An "information sharing platform" refers to a platform that provides repository information, such as that for open-source projects, and enables the collection of diverse software information.

[0339] "Program information" refers to technical information related to software and applications, including names, descriptions, and instruction sets.

[0340] A "set of instructions" refers to a series of program code written to control the operation of software.

[0341] "Summary information" refers to information that concisely expresses the main features and functions extracted from program information.

[0342] A "storage device" refers to a database system that stores generated summary information and related data, enabling efficient searching and retrieval.

[0343] A "user" refers to a person who inputs social issues and utilizes the service in order to receive software suggestions through the system.

[0344] "Characteristic terms" refer to highly relevant keywords and phrases extracted from the social issues entered by users.

[0345] "Program design" refers to new software ideas or solutions generated based on information obtained from an information sharing platform.

[0346] "Emotion recognition function" refers to technology that analyzes the user's emotional state and adjusts the suggested solutions accordingly.

[0347] This invention is a system that automatically collects program information from an information sharing platform and proposes the most suitable program design to the user by utilizing a generated AI model and emotion recognition function. This system runs as a software application on a general computer server and can be accessed by users from their terminals via a web browser.

[0348] In this system, the server retrieves program information from an information sharing platform (for example, a common open-source platform) using an API. Specific information includes the project name, description, instruction set (source code), and related technical information. To efficiently analyze and store this data, the server uses a database system (for example, a MySQL database) to store the information.

[0349] The server then uses a generative AI model (for example, the "GPT" model) to analyze the acquired set of instructions. It is prompted with the message, "Please briefly summarize the project's objectives and characteristics," and generates a concise summary.

[0350] The user inputs text about a social issue they want to solve using a terminal. The terminal analyzes the user input and extracts key words. These key words are sent to a server, which searches its database and suggests relevant program ideas.

[0351] The emotion recognition function operates on the server, analyzing the user's emotional state from their input and responses. Based on this data, the proposed program design is adjusted to match the user's emotions. For example, if a user is looking for software related to "improving digital access for the elderly," the emotion engine analyzes the user's expectations and proposes software ideas accordingly. In this way, optimal suggestions for the user become possible.

[0352] This system features a unique mechanism for providing more effective and relevant software solutions based on the individual needs and emotions of each user.

[0353] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0354] Step 1:

[0355] The server collects program information from the information sharing platform. Specifically, it periodically calls repository information using the information sharing platform's API to retrieve program information. It uses API keys and repository URLs as input and obtains program information such as project name, description, and command set as output.

[0356] Step 2:

[0357] The server sends data to a generating AI model to analyze the acquired program information and instruction set. The generating AI model analyzes the instruction set using the prompt statement "Please briefly summarize the project's objectives and characteristics" and generates summary information. The instruction set and prompt statement are used as input, and the generated summary information is obtained as output.

[0358] Step 3:

[0359] The server stores the generated summary information in a storage device. This process utilizes a database system to efficiently organize the information, facilitating subsequent searching and retrieval. The generated summary information is used as input, and the output is a status indicating that saving to the database is complete.

[0360] Step 4:

[0361] The user inputs a social issue they want to solve in text format using a device. The input issue is analyzed by the device, and relevant characteristic words are extracted. The user's text data is used as input, and a list of extracted characteristic words is obtained as output.

[0362] Step 5:

[0363] The server analyzes the list of characteristic words received from the terminal and searches its storage device. It finds relevant program ideas and creates a list of suggestions. The input is a list of characteristic words, and the output is a list of relevant program ideas.

[0364] Step 6:

[0365] The server analyzes the user's emotional state using emotion recognition. Based on this, it adjusts the proposed program design and creates an optimal list of suggestions. The user's input data and response data are used as input, and the adjusted list of suggestions is obtained as output.

[0366] Step 7:

[0367] Users can view visually organized proposals through their devices and see details of software ideas. The input is a list of proposals sent from the server, and the output is feedback tailored to the user's understanding and interests.

[0368] (Application Example 2)

[0369] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0370] In modern society, there is a need for systems that can analyze individual emotions in real time and provide optimal life support solutions. In particular, for the elderly and in situations with significant emotional fluctuations, the challenge lies in quickly proposing appropriate software and services tailored to the user. However, existing systems lack sufficient accuracy and efficiency in both emotion analysis and software recommendation, and are unable to meet the diverse needs of users.

[0371] 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.

[0372] In this invention, the server includes means for collecting information from an open platform, means for analyzing the data of the software information and generating summary information, and means for analyzing emotions and adjusting the suggested content. This makes it possible to suggest optimal life support resources based on the user's emotional state and individual needs.

[0373] An "open platform" is a publicly accessible collection of information, a space on the internet for providing software and data.

[0374] "Means of collecting information" refers to the methods and techniques for gathering data, and in particular, the process of obtaining useful data from resources on the internet.

[0375] "Means for analyzing data and generating summary information" refers to technologies that analyze acquired data, concisely summarize the necessary information, and generate summary data.

[0376] "Methods for analyzing emotions and adjusting proposals" refers to technologies that analyze the user's emotional response and optimize the proposals provided based on that analysis.

[0377] "Means of proposing life support resources" refer to methods and technologies for presenting software and services that support individuals' daily lives.

[0378] The system of this invention mainly consists of a server, a terminal, and a user. The server is used to automatically collect necessary information from an open platform and analyze the data. A generative AI model is used for the analysis, which generates a summary of the software information and stores it in a database that enables efficient searching.

[0379] The terminal functions as an interface for users to input their challenges. Based on the challenges the user is facing, it extracts relevant keywords and sends them to the server. The server then searches its database based on this keyword information and suggests the most relevant software ideas and implementation methods.

[0380] Furthermore, the server uses an emotion analysis engine to evaluate the user's emotions in real time. This analysis makes it possible to adjust the recommendations based on the user's emotions. For example, if an elderly person feels stressed while preparing dinner, a relaxation music app can be recommended. In this way, the system proposes the most suitable life support resources for the user and provides services that meet the user's needs and emotions.

[0381] The process described above aims to efficiently find useful software and services for users and improve their quality of life. As a concrete example, consider a prompt message: "Simulate a scenario where an elderly person feels stressed while preparing dinner and a relaxation music app is recommended." Based on this information, a system is created that provides the most suitable suggestions to the user.

[0382] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0383] Step 1:

[0384] The server collects software information from open platforms. It receives data obtained from the platform's APIs as input, analyzes this data, and extracts the name, description, source code, and related technical information for each project. As output, it formats the collected information and prepares it for further processing.

[0385] Step 2:

[0386] The server analyzes the collected source code and generates summary data using a generative AI model. It receives the formatted information from step 1 as input and uses a data analysis algorithm to summarize the project's functions and characteristics. As output, it stores the generated summary data in a database that allows for efficient searching.

[0387] Step 3:

[0388] The user inputs the problem they want to solve via their device. The system receives the problem or issue in text format as input and extracts relevant keywords based on its content. The extracted keywords are then sent to the server as output and used for database searches.

[0389] Step 4:

[0390] The server searches the database using the keywords received in step 3 and suggests relevant software ideas. It receives keywords as input and queries the database to extract highly relevant summary data. As output, it prepares the extracted software ideas for use in the next process.

[0391] Step 5:

[0392] The server uses an emotion analysis engine to evaluate the user's emotions and adjust the suggestions accordingly. It receives user voice and facial expression data as input and uses an emotion analysis algorithm to identify the user's emotional state. As output, it provides evolved software suggestions tailored to that emotional state.

[0393] Step 6:

[0394] The user receives the final proposal via their device and visually confirms the specific implementation methods. The system receives the adjusted proposal as input and displays it in the user interface. As output, it displays the proposal in an easy-to-understand format and presents feasible options.

[0395] 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.

[0396] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0397] 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.

[0398] [Third Embodiment]

[0399] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0400] 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.

[0401] 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).

[0402] 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.

[0403] 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.

[0404] 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).

[0405] 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.

[0406] 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.

[0407] 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.

[0408] 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.

[0409] 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.

[0410] 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".

[0411] This invention provides a system for effectively proposing software ideas and implementation methods to solve specific social problems. This system is built on a server and accessible to users via terminals. The main components of the system are a data collection module, a code analysis module, a database module, and a search and proposal module.

[0412] The server uses APIs from open-source platforms to collect daily update information. This process is automated in the backend, and the server periodically retrieves new repository information and saves it to storage. The retrieved information includes the repository name, description, technologies used, and source code.

[0413] Next, the server analyzes the collected source code using a generating AI via a code analysis module. This process summarizes the key functions and technologies of the source code and systematically stores this summary data in a database. This stored summary data is then used in subsequent search and suggestion processes.

[0414] The user uses a terminal to input the social problem they want to solve into the system. The terminal receives the user input, extracts relevant keywords, and sends them to the server. Based on these keywords, the server searches its database for highly relevant software ideas and implementation methods.

[0415] Ultimately, the server presents solutions to the user based on the search results. The terminal visually displays this information to the user, allowing them to evaluate the presented ideas and utilize them for concrete implementation.

[0416] For example, if a user enters a challenge related to "optimizing renewable energy," the system will search its database for relevant projects and suggest repositories that provide optimization algorithms useful for energy management. With this information, the user can then efficiently develop a new energy management system by leveraging the code.

[0417] Thus, the present invention is an effective system that provides users with a means to efficiently solve social problems.

[0418] The following describes the processing flow.

[0419] Step 1:

[0420] The server uses APIs from open-source platforms to collect repository information. This information includes basic metadata, source code, and project descriptions for the repository. Collection is performed regularly to ensure the system has fresh data.

[0421] Step 2:

[0422] The server uses a generative AI model to analyze the retrieved source code. This analysis summarizes the functionality and technology stack used in each repository. The summarized data is concise yet contains important functional elements.

[0423] Step 3:

[0424] The server stores the generated summary data in a database. This database is structured to allow for quick access to user search queries, enabling efficient searching and recommendations.

[0425] Step 4:

[0426] Users input the social issues they want to solve through their device. The device analyzes the input text, extracts relevant keywords, and sends them to the server. The extraction process utilizes natural language processing technology to improve accuracy.

[0427] Step 5:

[0428] The server searches the database based on the received keywords. It lists relevant software ideas and generates summaries of their implementation methods. This process employs advanced filtering techniques to improve the accuracy of keyword matching.

[0429] Step 6:

[0430] The terminal displays the suggestions provided by the server to the user. The user can refer to details and implementation outlines of each presented software idea. The visually organized information facilitates user decision-making.

[0431] Step 7:

[0432] Users select from the presented proposals and download or implement their desired software project. This allows users to efficiently start developing new services and solutions.

[0433] (Example 1)

[0434] 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."

[0435] There is a need to provide information technology that efficiently solves social problems. However, conventional systems have a problem in that they cannot quickly provide useful solutions because they lack the appropriate collection and analysis of relevant information.

[0436] 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.

[0437] In this invention, the server includes means for collecting information from an information sharing infrastructure, means for analyzing the program description of the information and generating summary information, and means for storing the summary information in a storage device. This makes it possible to quickly search for and propose highly relevant technical solutions based on user requests.

[0438] An "information sharing platform" is a platform that makes information such as software and data publicly available, making it accessible to other systems and users.

[0439] "Information" refers to a set of data with a specific purpose or function, including source code and technical specifications that are collected and analyzed.

[0440] "Program description" refers to the code that describes the operation of software, and is the subject of analysis and summarization.

[0441] "Summary information" refers to an overview of important functions and technologies extracted from the analyzed program description.

[0442] A "storage device" is a storage medium or database that stores collected and analyzed information and summary information, and allows it to be searched and referenced when needed.

[0443] "Operator" refers to an individual or organization that attempts to solve social problems using a system.

[0444] A "social problem" is an issue or challenge that affects the public interest and is something that is attempted to be solved through systems.

[0445] "Words" are keywords or phrases extracted from the operator's input and are used for information retrieval and relevance evaluation.

[0446] A "concept" refers to a proposed software idea or technical method that can be used to solve a problem.

[0447] To implement this invention, the server needs to have a system in place to collect information from an information sharing platform. For this purpose, the server utilizes an API to obtain open-source information via an internet connection. The API used in this case is one provided by a code repository.

[0448] The server utilizes a generative AI model to analyze the collected information. This generative AI model automatically analyzes the provided program description and generates a summary of the information. The generated summary is then stored directly in a storage device. A relational database is used as the storage device. This will enable efficient data retrieval and suggestions in the future.

[0449] The user uses a terminal to input a social problem they want to solve into the system. For example, they might input a problem such as "optimization of renewable energy" and generate a prompt based on that problem. An example of a prompt might be, "Please propose an open-source project that implements an algorithm for optimizing renewable energy."

[0450] The terminal analyzes the input information, extracts relevant terms, and sends them to the server. The server searches for storage devices based on these terms and suggests relevant concepts to the user. The user can then proceed with specific software development or technology application based on the presented information.

[0451] The technologies and methods used throughout this system are designed to allow users to efficiently obtain necessary technical information, even without specific expertise. Therefore, it can play a role in supporting rapid decision-making and implementation in projects that advance information technology-based problem-solving.

[0452] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0453] Step 1:

[0454] The server collects information from an information sharing platform. The input is an API for code repositories accessible via the internet. The server calls the API to retrieve a list of software repositories. This process collects information such as the repository name, description, technologies used, and source code, and records it in storage.

[0455] Step 2:

[0456] The server analyzes the collected information using a generative AI model. The input is the repository information collected in step 1. The server passes the source code to the generative AI model, which analyzes important functions and technologies to create summary information. The output is the summary information, which is systematically stored in a database.

[0457] Step 3:

[0458] The user uses a terminal to input a social problem they wish to solve into the system. The input is the social issue the user types into the terminal. The terminal extracts relevant keywords from this input and sends them to the server. This process clarifies the user's intent and effectively guides the system's search function.

[0459] Step 4:

[0460] The server searches the database using the received terms. The input is the terms extracted in step 3. The server searches the database for summary information and selects the most relevant software concepts and implementation methods. The output is a set of ideas proposed to the user.

[0461] Step 5:

[0462] The terminal visually displays suggestions sent from the server to the user. The input consists of suggested ideas that the server has searched for and selected. The terminal displays this information on the screen, helping the user evaluate each suggestion and decide how to specifically use it. This step allows the user to make quick decisions based on the information provided.

[0463] (Application Example 1)

[0464] 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."

[0465] With the development of smart cities, many social challenges have become more complex, and solutions are needed. These challenges include optimizing resources, mitigating traffic congestion, and improving energy efficiency. To effectively solve these problems, it is essential to accurately combine various technologies and their implementation methods. However, it is often difficult for users to find appropriate technological ideas and implementation methods on their own due to a lack of knowledge and information. To improve this situation, there is a need to provide a system that automatically suggests appropriate technological ideas to users and supports the efficient resolution of social challenges.

[0466] 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.

[0467] In this invention, the server includes means for acquiring program information from an open-source technology sharing platform, means for analyzing the source code of the program information and generating summary information, and means for storing the summary information in an information management device. This enables users to efficiently acquire appropriate technical ideas and implementation methods for social issues related to urban functions.

[0468] An "open-source technology sharing platform" is a place that provides freely accessible technical information on the internet and shares information useful for the development of various programs and software.

[0469] "Program information" is a general term for information related to the code, technical specifications, and algorithms used in specific software or applications.

[0470] "Source code" refers to code written in a programming language used to implement a specific function, and is a set of commands that govern the operation of software.

[0471] "Summary information" refers to information that extracts important elements from detailed program information or source code and summarizes them concisely.

[0472] An "information management device" is a system or device for systematically storing and managing large amounts of data, and for making it quickly searchable and available when needed.

[0473] "Users" refer to individuals or organizations that use this system to seek technology and information for the purpose of solving specific problems.

[0474] "Issues related to urban functions" refer to all problems that need to be solved in order to improve the quality of life and efficiency in cities, and include traffic flow, efficient energy use, and waste management.

[0475] A "technical idea" refers to a new technical concept or method devised to solve a specific problem.

[0476] "Implementation method" refers to the procedures and processes necessary to incorporate a technical idea into a system or product in a concrete form.

[0477] The system realizing this invention consists of a network-connected server and a terminal operated by the user. The server automatically retrieves program information from an open-source technology sharing platform. This program information includes the source code, technical specifications, and information about the technologies used in the software and applications. The server analyzes the retrieved information using a code analysis module, extracts important elements, and generates summary information. This summary information is stored in an information management device for efficient data management and is later used for searching based on user input.

[0478] The user uses a terminal to input the social challenges they are currently facing. The terminal processes the input, extracts relevant keywords, and sends them to a server. Based on the received keywords, the server searches for information management devices and identifies relevant technological ideas and implementation methods. The server uses a generative AI model to evaluate multiple solutions and presents the best one to the user. Finally, the terminal presents the user with a summary, providing direction toward solving specific social challenges.

[0479] The main hardware consists of server devices for processing information and terminals for operating the user interface, while the software includes software for managing generative AI models and information management devices. Specifically, the server runs analysis programs written in Python, and the generative AI models use models such as GPT-4. For information management, a SQL-based database management system is used to efficiently store and retrieve information.

[0480] For example, if a user inputs a problem such as "How can we optimize urban energy consumption?", the server will search for relevant program information from the information management device and present technical ideas useful for optimizing energy management. An example of a prompt to the generating AI model in this case is as follows: "Problem: Optimizing urban energy consumption Goal: Efficient energy management Search: Energy management optimization algorithm"

[0481] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0482] Step 1:

[0483] The server automatically retrieves program information from open-source technology sharing platforms. During this retrieval process, it periodically collects newly published information using specific APIs and stores it as program data. This information includes the software's source code and technical specifications.

[0484] Step 2:

[0485] The server inputs the acquired program information into a code analysis module and performs the analysis. The analysis utilizes a generative AI model to identify key elements within the program information and generate summary information. At this stage, major functions and technical features are extracted and stored as summary information in the information management device.

[0486] Step 3:

[0487] The user uses a terminal to input the social issue they want to solve as text. The terminal performs basic natural language processing on the input issue to extract relevant keywords, which are then sent to the server.

[0488] Step 4:

[0489] The server uses the received keywords to search the information management device and identify relevant technical ideas and implementation methods. Here, a database search algorithm is used to extract highly relevant information from the summary information, while duplicate removal and importance evaluation of the results are performed in parallel.

[0490] Step 5:

[0491] The server evaluates multiple solutions based on technical ideas obtained using a generative AI model. It scores the options and determines the most appropriate technical idea and its implementation method. It generates prompts and sends them to the AI, and evaluates the responses to formulate the optimal solution.

[0492] Step 6:

[0493] The device presents the user with a summary of the optimal technical idea and implementation method. This summary is presented in a visually easy-to-understand format, serving as clear guidance on the user's next course of action.

[0494] 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.

[0495] This invention provides a system that automatically collects software information from open-source platforms and combines it with an emotion engine to suggest optimal software ideas to the user. The system runs on a server and is accessible to users via a terminal. The system's main components include a data collection module, a code analysis module, a database module, a search and suggestion module, and an emotion engine.

[0496] The server automatically collects repository information from open-source platforms. This is done using APIs, and the information is updated regularly. The collected information includes the project name, description, source code, and related technical information.

[0497] Next, the server analyzes the source code through a code analysis module and generates summary data using a generative AI model. This summary data concisely represents the project's functions and characteristics and is stored in a database. This database is designed to enable efficient searching and suggestions.

[0498] The user inputs a social issue they want to solve through a terminal. The terminal receives and analyzes this input, extracts relevant keywords, and sends them to the server. The server searches its database based on the received keywords and suggests relevant software ideas.

[0499] Furthermore, the emotion engine recognizes the user's emotions and adjusts the suggestions based on this information. For example, the emotion engine detects whether the user is excited or stressed and makes suggestions tailored to that state. This emotion data is stored in a database along with past suggestion history and used to optimize future suggestions.

[0500] Users receive suggested ideas via their devices and review visually organized information. For example, if a user is looking for software related to "improving digital access for seniors," the emotion engine analyzes the user's interests and suggests software and tools that meet this need. This process allows users to receive suggestions optimized for their emotions and needs, enabling them to quickly begin implementing new projects.

[0501] Thus, the present invention provides a unique system that enables users to find more appropriate and effective software solutions based on their emotions.

[0502] The following describes the processing flow.

[0503] Step 1:

[0504] The server automatically collects metadata and source code from each repository using the API of the open-source platform. This collection process is performed periodically to retrieve newly updated information.

[0505] Step 2:

[0506] The server analyzes the collected source code using an AI model. This summarizes the functionality of each repository, the technical resources used, and the characteristics of the project, generating summary data.

[0507] Step 3:

[0508] The server structures and stores the generated summary data in a database. This database is indexed to enable efficient searching and allows queries to be processed quickly.

[0509] Step 4:

[0510] The user uses a device to input the social issue they want to solve in natural language. The device receives this input, uses a text analysis tool to extract relevant keywords, and sends them to the server.

[0511] Step 5:

[0512] The server queries the database based on the received keywords to find relevant software ideas. The search results include summaries of the relevant projects and their implementation methods.

[0513] Step 6:

[0514] The terminal presents the user with results provided by the server. This includes a project overview, technology stack, expected effects, and implementation tips. The user also receives information related to their emotional state as perceived by the emotion engine.

[0515] Step 7:

[0516] The emotion engine analyzes user input and responses to identify the user's emotional state. For example, it determines whether the user is excited or calm based on text and interactions.

[0517] Step 8:

[0518] The server uses emotion data recognized by the emotion engine to refine the software ideas it proposes. Based on the user's emotions, it prioritizes presenting ideas that are more likely to be accepted by the user.

[0519] Step 9:

[0520] The user reviews the refined proposals and selects the software idea they deem best. Based on this, they begin implementing the project. The selected proposal has a mechanism to provide feedback for later improvement.

[0521] (Example 2)

[0522] 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."

[0523] In modern society, while a wide variety of software is being developed, it has become difficult to quickly and appropriately find the necessary software solutions. Furthermore, there is a lack of systems that provide solution suggestions optimized for the user's emotional state, so users often receive suggestions that do not fully meet their needs. This invention aims to solve these problems.

[0524] 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.

[0525] In this invention, the server includes means for collecting program information from an information sharing platform, means for analyzing the instruction set of the program information and generating summary information, and means for storing the summary information in a storage device. This makes it possible to quickly and appropriately propose relevant program designs in response to social issues input by the user and to provide optimal solutions that correspond to the user's emotional state.

[0526] An "information sharing platform" refers to a platform that provides repository information, such as that for open-source projects, and enables the collection of diverse software information.

[0527] "Program information" refers to technical information related to software and applications, including names, descriptions, and instruction sets.

[0528] A "set of instructions" refers to a series of program code written to control the operation of software.

[0529] "Summary information" refers to information that concisely expresses the main features and functions extracted from program information.

[0530] A "storage device" refers to a database system that stores generated summary information and related data, enabling efficient searching and retrieval.

[0531] A "user" refers to a person who inputs social issues and utilizes the service in order to receive software suggestions through the system.

[0532] "Characteristic terms" refer to highly relevant keywords and phrases extracted from the social issues entered by users.

[0533] "Program design" refers to new software ideas or solutions generated based on information obtained from an information sharing platform.

[0534] "Emotion recognition function" refers to technology that analyzes the user's emotional state and adjusts the suggested solutions accordingly.

[0535] This invention is a system that automatically collects program information from an information sharing platform and proposes the most suitable program design to the user by utilizing a generated AI model and emotion recognition function. This system runs as a software application on a general computer server and can be accessed by users from their terminals via a web browser.

[0536] In this system, the server retrieves program information from an information sharing platform (for example, a common open-source platform) using an API. Specific information includes the project name, description, instruction set (source code), and related technical information. To efficiently analyze and store this data, the server uses a database system (for example, a MySQL database) to store the information.

[0537] The server then uses a generative AI model (for example, the "GPT" model) to analyze the acquired set of instructions. It is prompted with the message, "Please briefly summarize the project's objectives and characteristics," and generates a concise summary.

[0538] The user inputs text about a social issue they want to solve using a terminal. The terminal analyzes the user input and extracts key words. These key words are sent to a server, which searches its database and suggests relevant program ideas.

[0539] The emotion recognition function operates on the server, analyzing the user's emotional state from their input and responses. Based on this data, the proposed program design is adjusted to match the user's emotions. For example, if a user is looking for software related to "improving digital access for the elderly," the emotion engine analyzes the user's expectations and proposes software ideas accordingly. In this way, optimal suggestions for the user become possible.

[0540] This system features a unique mechanism for providing more effective and relevant software solutions based on the individual needs and emotions of each user.

[0541] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0542] Step 1:

[0543] The server collects program information from the information sharing platform. Specifically, it periodically calls repository information using the information sharing platform's API to retrieve program information. It uses API keys and repository URLs as input and obtains program information such as project name, description, and command set as output.

[0544] Step 2:

[0545] The server sends data to a generating AI model to analyze the acquired program information and instruction set. The generating AI model analyzes the instruction set using the prompt statement "Please briefly summarize the project's objectives and characteristics" and generates summary information. The instruction set and prompt statement are used as input, and the generated summary information is obtained as output.

[0546] Step 3:

[0547] The server stores the generated summary information in a storage device. This process utilizes a database system to efficiently organize the information, facilitating subsequent searching and retrieval. The generated summary information is used as input, and the output is a status indicating that saving to the database is complete.

[0548] Step 4:

[0549] The user inputs a social issue they want to solve in text format using a device. The input issue is analyzed by the device, and relevant characteristic words are extracted. The user's text data is used as input, and a list of extracted characteristic words is obtained as output.

[0550] Step 5:

[0551] The server analyzes the list of characteristic words received from the terminal and searches its storage device. It finds relevant program ideas and creates a list of suggestions. The input is a list of characteristic words, and the output is a list of relevant program ideas.

[0552] Step 6:

[0553] The server analyzes the user's emotional state using emotion recognition. Based on this, it adjusts the proposed program design and creates an optimal list of suggestions. The user's input data and response data are used as input, and the adjusted list of suggestions is obtained as output.

[0554] Step 7:

[0555] Users can view visually organized proposals through their devices and see details of software ideas. The input is a list of proposals sent from the server, and the output is feedback tailored to the user's understanding and interests.

[0556] (Application Example 2)

[0557] 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."

[0558] In modern society, there is a need for systems that can analyze individual emotions in real time and provide optimal life support solutions. In particular, for the elderly and in situations with significant emotional fluctuations, the challenge lies in quickly proposing appropriate software and services tailored to the user. However, existing systems lack sufficient accuracy and efficiency in both emotion analysis and software recommendation, and are unable to meet the diverse needs of users.

[0559] 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.

[0560] In this invention, the server includes means for collecting information from an open platform, means for analyzing the data of the software information and generating summary information, and means for analyzing emotions and adjusting the suggested content. This makes it possible to suggest optimal life support resources based on the user's emotional state and individual needs.

[0561] An "open platform" is a publicly accessible collection of information, a space on the internet for providing software and data.

[0562] "Means of collecting information" refers to the methods and techniques for gathering data, and in particular, the process of obtaining useful data from resources on the internet.

[0563] "Means for analyzing data and generating summary information" refers to technologies that analyze acquired data, concisely summarize the necessary information, and generate summary data.

[0564] "Methods for analyzing emotions and adjusting proposals" refers to technologies that analyze the user's emotional response and optimize the proposals provided based on that analysis.

[0565] "Means of proposing life support resources" refer to methods and technologies for presenting software and services that support individuals' daily lives.

[0566] The system of this invention mainly consists of a server, a terminal, and a user. The server is used to automatically collect necessary information from an open platform and analyze the data. A generative AI model is used for the analysis, which generates a summary of the software information and stores it in a database that enables efficient searching.

[0567] The terminal functions as an interface for users to input their challenges. Based on the challenges the user is facing, it extracts relevant keywords and sends them to the server. The server then searches its database based on this keyword information and suggests the most relevant software ideas and implementation methods.

[0568] Furthermore, the server uses an emotion analysis engine to evaluate the user's emotions in real time. This analysis makes it possible to adjust the recommendations based on the user's emotions. For example, if an elderly person feels stressed while preparing dinner, a relaxation music app can be recommended. In this way, the system proposes the most suitable life support resources for the user and provides services that meet the user's needs and emotions.

[0569] The process described above aims to efficiently find useful software and services for users and improve their quality of life. As a concrete example, consider a prompt message: "Simulate a scenario where an elderly person feels stressed while preparing dinner and a relaxation music app is recommended." Based on this information, a system is created that provides the most suitable suggestions to the user.

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

[0571] Step 1:

[0572] The server collects software information from open platforms. It receives data obtained from the platform's APIs as input, analyzes this data, and extracts the name, description, source code, and related technical information for each project. As output, it formats the collected information and prepares it for further processing.

[0573] Step 2:

[0574] The server analyzes the collected source code and generates summary data using a generative AI model. It receives the formatted information from step 1 as input and uses a data analysis algorithm to summarize the project's functions and characteristics. As output, it stores the generated summary data in a database that allows for efficient searching.

[0575] Step 3:

[0576] The user inputs the problem they want to solve via their device. The system receives the problem or issue in text format as input and extracts relevant keywords based on its content. The extracted keywords are then sent to the server as output and used for database searches.

[0577] Step 4:

[0578] The server searches the database using the keywords received in step 3 and suggests relevant software ideas. It receives keywords as input and queries the database to extract highly relevant summary data. As output, it prepares the extracted software ideas for use in the next process.

[0579] Step 5:

[0580] The server uses an emotion analysis engine to evaluate the user's emotions and adjust the suggestions accordingly. It receives user voice and facial expression data as input and uses an emotion analysis algorithm to identify the user's emotional state. As output, it provides evolved software suggestions tailored to that emotional state.

[0581] Step 6:

[0582] The user receives the final proposal via their device and visually confirms the specific implementation methods. The system receives the adjusted proposal as input and displays it in the user interface. As output, it displays the proposal in an easy-to-understand format and presents feasible options.

[0583] 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.

[0584] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0585] 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.

[0586] [Fourth Embodiment]

[0587] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0588] 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.

[0589] 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).

[0590] 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.

[0591] 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.

[0592] 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).

[0593] 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.

[0594] 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.

[0595] 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.

[0596] 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.

[0597] 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.

[0598] 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.

[0599] 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".

[0600] This invention provides a system for effectively proposing software ideas and implementation methods to solve specific social problems. This system is built on a server and accessible to users via terminals. The main components of the system are a data collection module, a code analysis module, a database module, and a search and proposal module.

[0601] The server uses APIs from open-source platforms to collect daily update information. This process is automated in the backend, and the server periodically retrieves new repository information and saves it to storage. The retrieved information includes the repository name, description, technologies used, and source code.

[0602] Next, the server analyzes the collected source code using a generating AI via a code analysis module. This process summarizes the key functions and technologies of the source code and systematically stores this summary data in a database. This stored summary data is then used in subsequent search and suggestion processes.

[0603] The user uses a terminal to input the social problem they want to solve into the system. The terminal receives the user input, extracts relevant keywords, and sends them to the server. Based on these keywords, the server searches its database for highly relevant software ideas and implementation methods.

[0604] Ultimately, the server presents solutions to the user based on the search results. The terminal visually displays this information to the user, allowing them to evaluate the presented ideas and utilize them for concrete implementation.

[0605] For example, if a user enters a challenge related to "optimizing renewable energy," the system will search its database for relevant projects and suggest repositories that provide optimization algorithms useful for energy management. With this information, the user can then efficiently develop a new energy management system by leveraging the code.

[0606] Thus, the present invention is an effective system that provides users with a means to efficiently solve social problems.

[0607] The following describes the processing flow.

[0608] Step 1:

[0609] The server uses APIs from open-source platforms to collect repository information. This information includes basic metadata, source code, and project descriptions for the repository. Collection is performed regularly to ensure the system has fresh data.

[0610] Step 2:

[0611] The server uses a generative AI model to analyze the retrieved source code. This analysis summarizes the functionality and technology stack used in each repository. The summarized data is concise yet contains important functional elements.

[0612] Step 3:

[0613] The server stores the generated summary data in a database. This database is structured to allow for quick access to user search queries, enabling efficient searching and recommendations.

[0614] Step 4:

[0615] Users input the social issues they want to solve through their device. The device analyzes the input text, extracts relevant keywords, and sends them to the server. The extraction process utilizes natural language processing technology to improve accuracy.

[0616] Step 5:

[0617] The server searches the database based on the received keywords. It lists relevant software ideas and generates summaries of their implementation methods. This process employs advanced filtering techniques to improve the accuracy of keyword matching.

[0618] Step 6:

[0619] The terminal displays the suggestions provided by the server to the user. The user can refer to details and implementation outlines of each presented software idea. The visually organized information facilitates user decision-making.

[0620] Step 7:

[0621] Users select from the presented proposals and download or implement their desired software project. This allows users to efficiently start developing new services and solutions.

[0622] (Example 1)

[0623] 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".

[0624] There is a need to provide information technology that efficiently solves social problems. However, conventional systems have a problem in that they cannot quickly provide useful solutions because they lack the appropriate collection and analysis of relevant information.

[0625] 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.

[0626] In this invention, the server includes means for collecting information from an information sharing infrastructure, means for analyzing the program description of the information and generating summary information, and means for storing the summary information in a storage device. This makes it possible to quickly search for and propose highly relevant technical solutions based on user requests.

[0627] An "information sharing platform" is a platform that makes information such as software and data publicly available, making it accessible to other systems and users.

[0628] "Information" refers to a set of data with a specific purpose or function, including source code and technical specifications that are collected and analyzed.

[0629] "Program description" refers to the code that describes the operation of software, and is the subject of analysis and summarization.

[0630] "Summary information" refers to an overview of important functions and technologies extracted from the analyzed program description.

[0631] A "storage device" is a storage medium or database that stores collected and analyzed information and summary information, and allows it to be searched and referenced when needed.

[0632] "Operator" refers to an individual or organization that attempts to solve social problems using a system.

[0633] A "social problem" is an issue or challenge that affects the public interest and is something that is attempted to be solved through systems.

[0634] "Words" are keywords or phrases extracted from the operator's input and are used for information retrieval and relevance evaluation.

[0635] A "concept" refers to a proposed software idea or technical method that can be used to solve a problem.

[0636] To implement this invention, the server needs to have a system in place to collect information from an information sharing platform. For this purpose, the server utilizes an API to obtain open-source information via an internet connection. The API used in this case is one provided by a code repository.

[0637] The server utilizes a generative AI model to analyze the collected information. This generative AI model automatically analyzes the provided program description and generates a summary of the information. The generated summary is then stored directly in a storage device. A relational database is used as the storage device. This will enable efficient data retrieval and suggestions in the future.

[0638] The user uses a terminal to input a social problem they want to solve into the system. For example, they might input a problem such as "optimization of renewable energy" and generate a prompt based on that problem. An example of a prompt might be, "Please propose an open-source project that implements an algorithm for optimizing renewable energy."

[0639] The terminal analyzes the input information, extracts relevant terms, and sends them to the server. The server searches for storage devices based on these terms and suggests relevant concepts to the user. The user can then proceed with specific software development or technology application based on the presented information.

[0640] The technologies and methods used throughout this system are designed to allow users to efficiently obtain necessary technical information, even without specific expertise. Therefore, it can play a role in supporting rapid decision-making and implementation in projects that advance information technology-based problem-solving.

[0641] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0642] Step 1:

[0643] The server collects information from an information sharing platform. The input is an API for code repositories accessible via the internet. The server calls the API to retrieve a list of software repositories. This process collects information such as the repository name, description, technologies used, and source code, and records it in storage.

[0644] Step 2:

[0645] The server analyzes the collected information using a generative AI model. The input is the repository information collected in step 1. The server passes the source code to the generative AI model, which analyzes important functions and technologies to create summary information. The output is the summary information, which is systematically stored in a database.

[0646] Step 3:

[0647] The user uses a terminal to input a social problem they wish to solve into the system. The input is the social issue the user types into the terminal. The terminal extracts relevant keywords from this input and sends them to the server. This process clarifies the user's intent and effectively guides the system's search function.

[0648] Step 4:

[0649] The server searches the database using the received terms. The input is the terms extracted in step 3. The server searches the database for summary information and selects the most relevant software concepts and implementation methods. The output is a set of ideas proposed to the user.

[0650] Step 5:

[0651] The terminal visually displays suggestions sent from the server to the user. The input consists of suggested ideas that the server has searched for and selected. The terminal displays this information on the screen, helping the user evaluate each suggestion and decide how to specifically use it. This step allows the user to make quick decisions based on the information provided.

[0652] (Application Example 1)

[0653] 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".

[0654] With the development of smart cities, many social challenges have become more complex, and solutions are needed. These challenges include optimizing resources, mitigating traffic congestion, and improving energy efficiency. To effectively solve these problems, it is essential to accurately combine various technologies and their implementation methods. However, it is often difficult for users to find appropriate technological ideas and implementation methods on their own due to a lack of knowledge and information. To improve this situation, there is a need to provide a system that automatically suggests appropriate technological ideas to users and supports the efficient resolution of social challenges.

[0655] 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.

[0656] In this invention, the server includes means for acquiring program information from an open-source technology sharing platform, means for analyzing the source code of the program information and generating summary information, and means for storing the summary information in an information management device. This enables users to efficiently acquire appropriate technical ideas and implementation methods for social issues related to urban functions.

[0657] An "open-source technology sharing platform" is a place that provides freely accessible technical information on the internet and shares information useful for the development of various programs and software.

[0658] "Program information" is a general term for information related to the code, technical specifications, and algorithms used in specific software or applications.

[0659] "Source code" refers to code written in a programming language used to implement a specific function, and is a set of commands that govern the operation of software.

[0660] "Summary information" refers to information that extracts important elements from detailed program information or source code and summarizes them concisely.

[0661] An "information management device" is a system or device for systematically storing and managing large amounts of data, and for making it quickly searchable and available when needed.

[0662] "Users" refer to individuals or organizations that use this system to seek technology and information for the purpose of solving specific problems.

[0663] "Issues related to urban functions" refer to all problems that need to be solved in order to improve the quality of life and efficiency in cities, and include traffic flow, efficient energy use, and waste management.

[0664] A "technical idea" refers to a new technical concept or method devised to solve a specific problem.

[0665] "Implementation method" refers to the procedures and processes necessary to incorporate a technical idea into a system or product in a concrete form.

[0666] The system realizing this invention consists of a network-connected server and a terminal operated by the user. The server automatically retrieves program information from an open-source technology sharing platform. This program information includes the source code, technical specifications, and information about the technologies used in the software and applications. The server analyzes the retrieved information using a code analysis module, extracts important elements, and generates summary information. This summary information is stored in an information management device for efficient data management and is later used for searching based on user input.

[0667] The user uses a terminal to input the social challenges they are currently facing. The terminal processes the input, extracts relevant keywords, and sends them to a server. Based on the received keywords, the server searches for information management devices and identifies relevant technological ideas and implementation methods. The server uses a generative AI model to evaluate multiple solutions and presents the best one to the user. Finally, the terminal presents the user with a summary, providing direction toward solving specific social challenges.

[0668] The main hardware consists of server devices for processing information and terminals for operating the user interface, while the software includes software for managing generative AI models and information management devices. Specifically, the server runs analysis programs written in Python, and the generative AI models use models such as GPT-4. For information management, a SQL-based database management system is used to efficiently store and retrieve information.

[0669] For example, if a user inputs a problem such as "How can we optimize urban energy consumption?", the server will search for relevant program information from the information management device and present technical ideas useful for optimizing energy management. An example of a prompt to the generating AI model in this case is as follows: "Problem: Optimizing urban energy consumption Goal: Efficient energy management Search: Energy management optimization algorithm"

[0670] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0671] Step 1:

[0672] The server automatically retrieves program information from open-source technology sharing platforms. During this retrieval process, it periodically collects newly published information using specific APIs and stores it as program data. This information includes the software's source code and technical specifications.

[0673] Step 2:

[0674] The server inputs the acquired program information into a code analysis module and performs the analysis. The analysis utilizes a generative AI model to identify key elements within the program information and generate summary information. At this stage, major functions and technical features are extracted and stored as summary information in the information management device.

[0675] Step 3:

[0676] The user uses a terminal to input the social issue they want to solve as text. The terminal performs basic natural language processing on the input issue to extract relevant keywords, which are then sent to the server.

[0677] Step 4:

[0678] The server uses the received keywords to search the information management device and identify relevant technical ideas and implementation methods. Here, a database search algorithm is used to extract highly relevant information from the summary information, while duplicate removal and importance evaluation of the results are performed in parallel.

[0679] Step 5:

[0680] The server evaluates multiple solutions based on technical ideas obtained using a generative AI model. It scores the options and determines the most appropriate technical idea and its implementation method. It generates prompts and sends them to the AI, and evaluates the responses to formulate the optimal solution.

[0681] Step 6:

[0682] The device presents the user with a summary of the optimal technical idea and implementation method. This summary is presented in a visually easy-to-understand format, serving as clear guidance on the user's next course of action.

[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 provides a system that automatically collects software information from open-source platforms and combines it with an emotion engine to suggest optimal software ideas to the user. The system runs on a server and is accessible to users via a terminal. The system's main components include a data collection module, a code analysis module, a database module, a search and suggestion module, and an emotion engine.

[0685] The server automatically collects repository information from open-source platforms. This is done using APIs, and the information is updated regularly. The collected information includes the project name, description, source code, and related technical information.

[0686] Next, the server analyzes the source code through a code analysis module and generates summary data using a generative AI model. This summary data concisely represents the project's functions and characteristics and is stored in a database. This database is designed to enable efficient searching and suggestions.

[0687] The user inputs a social issue they want to solve through a terminal. The terminal receives and analyzes this input, extracts relevant keywords, and sends them to the server. The server searches its database based on the received keywords and suggests relevant software ideas.

[0688] Furthermore, the emotion engine recognizes the user's emotions and adjusts the suggestions based on this information. For example, the emotion engine detects whether the user is excited or stressed and makes suggestions tailored to that state. This emotion data is stored in a database along with past suggestion history and used to optimize future suggestions.

[0689] Users receive suggested ideas via their devices and review visually organized information. For example, if a user is looking for software related to "improving digital access for seniors," the emotion engine analyzes the user's interests and suggests software and tools that meet this need. This process allows users to receive suggestions optimized for their emotions and needs, enabling them to quickly begin implementing new projects.

[0690] Thus, the present invention provides a unique system that enables users to find more appropriate and effective software solutions based on their emotions.

[0691] The following describes the processing flow.

[0692] Step 1:

[0693] The server automatically collects metadata and source code from each repository using the API of the open-source platform. This collection process is performed periodically to retrieve newly updated information.

[0694] Step 2:

[0695] The server analyzes the collected source code using an AI model. This summarizes the functionality of each repository, the technical resources used, and the characteristics of the project, generating summary data.

[0696] Step 3:

[0697] The server structures and stores the generated summary data in a database. This database is indexed to enable efficient searching and allows queries to be processed quickly.

[0698] Step 4:

[0699] The user uses a device to input the social issue they want to solve in natural language. The device receives this input, uses a text analysis tool to extract relevant keywords, and sends them to the server.

[0700] Step 5:

[0701] The server queries the database based on the received keywords to find relevant software ideas. The search results include summaries of the relevant projects and their implementation methods.

[0702] Step 6:

[0703] The terminal presents the user with results provided by the server. This includes a project overview, technology stack, expected effects, and implementation tips. The user also receives information related to their emotional state as perceived by the emotion engine.

[0704] Step 7:

[0705] The emotion engine analyzes user input and responses to identify the user's emotional state. For example, it determines whether the user is excited or calm based on text and interactions.

[0706] Step 8:

[0707] The server uses emotion data recognized by the emotion engine to refine the software ideas it proposes. Based on the user's emotions, it prioritizes presenting ideas that are more likely to be accepted by the user.

[0708] Step 9:

[0709] The user reviews the refined proposals and selects the software idea they deem best. Based on this, they begin implementing the project. The selected proposal has a mechanism to provide feedback for later improvement.

[0710] (Example 2)

[0711] 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".

[0712] In modern society, while a wide variety of software is being developed, it has become difficult to quickly and appropriately find the necessary software solutions. Furthermore, there is a lack of systems that provide solution suggestions optimized for the user's emotional state, so users often receive suggestions that do not fully meet their needs. This invention aims to solve these problems.

[0713] 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.

[0714] In this invention, the server includes means for collecting program information from an information sharing platform, means for analyzing the instruction set of the program information and generating summary information, and means for storing the summary information in a storage device. This makes it possible to quickly and appropriately propose relevant program designs in response to social issues input by the user and to provide optimal solutions that correspond to the user's emotional state.

[0715] An "information sharing platform" refers to a platform that provides repository information, such as that for open-source projects, and enables the collection of diverse software information.

[0716] "Program information" refers to technical information related to software and applications, including names, descriptions, and instruction sets.

[0717] A "set of instructions" refers to a series of program code written to control the operation of software.

[0718] "Summary information" refers to information that concisely expresses the main features and functions extracted from program information.

[0719] A "storage device" refers to a database system that stores generated summary information and related data, enabling efficient searching and retrieval.

[0720] A "user" refers to a person who inputs social issues and utilizes the service in order to receive software suggestions through the system.

[0721] "Characteristic terms" refer to highly relevant keywords and phrases extracted from the social issues entered by users.

[0722] "Program design" refers to new software ideas or solutions generated based on information obtained from an information sharing platform.

[0723] "Emotion recognition function" refers to technology that analyzes the user's emotional state and adjusts the suggested solutions accordingly.

[0724] This invention is a system that automatically collects program information from an information sharing platform and proposes the most suitable program design to the user by utilizing a generated AI model and emotion recognition function. This system runs as a software application on a general computer server and can be accessed by users from their terminals via a web browser.

[0725] In this system, the server retrieves program information from an information sharing platform (for example, a common open-source platform) using an API. Specific information includes the project name, description, instruction set (source code), and related technical information. To efficiently analyze and store this data, the server uses a database system (for example, a MySQL database) to store the information.

[0726] The server then uses a generative AI model (for example, the "GPT" model) to analyze the acquired set of instructions. It is prompted with the message, "Please briefly summarize the project's objectives and characteristics," and generates a concise summary.

[0727] The user inputs text about a social issue they want to solve using a terminal. The terminal analyzes the user input and extracts key words. These key words are sent to a server, which searches its database and suggests relevant program ideas.

[0728] The emotion recognition function operates on the server, analyzing the user's emotional state from their input and responses. Based on this data, the proposed program design is adjusted to match the user's emotions. For example, if a user is looking for software related to "improving digital access for the elderly," the emotion engine analyzes the user's expectations and proposes software ideas accordingly. In this way, optimal suggestions for the user become possible.

[0729] This system features a unique mechanism for providing more effective and relevant software solutions based on the individual needs and emotions of each user.

[0730] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0731] Step 1:

[0732] The server collects program information from the information sharing platform. Specifically, it periodically calls repository information using the information sharing platform's API to retrieve program information. It uses API keys and repository URLs as input and obtains program information such as project name, description, and command set as output.

[0733] Step 2:

[0734] The server sends data to a generating AI model to analyze the acquired program information and instruction set. The generating AI model analyzes the instruction set using the prompt statement "Please briefly summarize the project's objectives and characteristics" and generates summary information. The instruction set and prompt statement are used as input, and the generated summary information is obtained as output.

[0735] Step 3:

[0736] The server stores the generated summary information in a storage device. This process utilizes a database system to efficiently organize the information, facilitating subsequent searching and retrieval. The generated summary information is used as input, and the output is a status indicating that saving to the database is complete.

[0737] Step 4:

[0738] The user inputs a social issue they want to solve in text format using a device. The input issue is analyzed by the device, and relevant characteristic words are extracted. The user's text data is used as input, and a list of extracted characteristic words is obtained as output.

[0739] Step 5:

[0740] The server analyzes the list of characteristic words received from the terminal and searches its storage device. It finds relevant program ideas and creates a list of suggestions. The input is a list of characteristic words, and the output is a list of relevant program ideas.

[0741] Step 6:

[0742] The server analyzes the user's emotional state using emotion recognition. Based on this, it adjusts the proposed program design and creates an optimal list of suggestions. The user's input data and response data are used as input, and the adjusted list of suggestions is obtained as output.

[0743] Step 7:

[0744] Users can view visually organized proposals through their devices and see details of software ideas. The input is a list of proposals sent from the server, and the output is feedback tailored to the user's understanding and interests.

[0745] (Application Example 2)

[0746] 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".

[0747] In modern society, there is a need for systems that can analyze individual emotions in real time and provide optimal life support solutions. In particular, for the elderly and in situations with significant emotional fluctuations, the challenge lies in quickly proposing appropriate software and services tailored to the user. However, existing systems lack sufficient accuracy and efficiency in both emotion analysis and software recommendation, and are unable to meet the diverse needs of users.

[0748] 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.

[0749] In this invention, the server includes means for collecting information from an open platform, means for analyzing the data of the software information and generating summary information, and means for analyzing emotions and adjusting the suggested content. This makes it possible to suggest optimal life support resources based on the user's emotional state and individual needs.

[0750] An "open platform" is a publicly accessible collection of information, a space on the internet for providing software and data.

[0751] "Means of collecting information" refers to the methods and techniques for gathering data, and in particular, the process of obtaining useful data from resources on the internet.

[0752] "Means for analyzing data and generating summary information" refers to technologies that analyze acquired data, concisely summarize the necessary information, and generate summary data.

[0753] "Methods for analyzing emotions and adjusting proposals" refers to technologies that analyze the user's emotional response and optimize the proposals provided based on that analysis.

[0754] "Means of proposing life support resources" refer to methods and technologies for presenting software and services that support individuals' daily lives.

[0755] The system of this invention mainly consists of a server, a terminal, and a user. The server is used to automatically collect necessary information from an open platform and analyze the data. A generative AI model is used for the analysis, which generates a summary of the software information and stores it in a database that enables efficient searching.

[0756] The terminal functions as an interface for users to input their challenges. Based on the challenges the user is facing, it extracts relevant keywords and sends them to the server. The server then searches its database based on this keyword information and suggests the most relevant software ideas and implementation methods.

[0757] Furthermore, the server uses an emotion analysis engine to evaluate the user's emotions in real time. This analysis makes it possible to adjust the recommendations based on the user's emotions. For example, if an elderly person feels stressed while preparing dinner, a relaxation music app can be recommended. In this way, the system proposes the most suitable life support resources for the user and provides services that meet the user's needs and emotions.

[0758] The process described above aims to efficiently find useful software and services for users and improve their quality of life. As a concrete example, consider a prompt message: "Simulate a scenario where an elderly person feels stressed while preparing dinner and a relaxation music app is recommended." Based on this information, a system is created that provides the most suitable suggestions to the user.

[0759] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0760] Step 1:

[0761] The server collects software information from open platforms. It receives data obtained from the platform's APIs as input, analyzes this data, and extracts the name, description, source code, and related technical information for each project. As output, it formats the collected information and prepares it for further processing.

[0762] Step 2:

[0763] The server analyzes the collected source code and generates summary data using a generative AI model. It receives the formatted information from step 1 as input and uses a data analysis algorithm to summarize the project's functions and characteristics. As output, it stores the generated summary data in a database that allows for efficient searching.

[0764] Step 3:

[0765] The user inputs the problem they want to solve via their device. The system receives the problem or issue in text format as input and extracts relevant keywords based on its content. The extracted keywords are then sent to the server as output and used for database searches.

[0766] Step 4:

[0767] The server searches the database using the keywords received in step 3 and suggests relevant software ideas. It receives keywords as input and queries the database to extract highly relevant summary data. As output, it prepares the extracted software ideas for use in the next process.

[0768] Step 5:

[0769] The server uses an emotion analysis engine to evaluate the user's emotions and adjust the suggestions accordingly. It receives user voice and facial expression data as input and uses an emotion analysis algorithm to identify the user's emotional state. As output, it provides evolved software suggestions tailored to that emotional state.

[0770] Step 6:

[0771] The user receives the final proposal via their device and visually confirms the specific implementation methods. The system receives the adjusted proposal as input and displays it in the user interface. As output, it displays the proposal in an easy-to-understand format and presents feasible options.

[0772] 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.

[0773] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). An 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.

[0774] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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.

[0779] 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.

[0780] 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."

[0781] 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.

[0782] 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.

[0783] 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.

[0784] 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.

[0785] 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.

[0786] 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.

[0787] 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.

[0788] 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.

[0789] 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.

[0790] 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.

[0791] 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.

[0792] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0793] The following is further disclosed regarding the embodiments described above.

[0794] (Claim 1)

[0795] Means of collecting software information from open-source platforms,

[0796] A means for analyzing the source code of the software information and generating summary data,

[0797] Means for storing the summary data in a database,

[0798] A method for extracting relevant keywords from social issues entered by users,

[0799] A means of searching a database using the keyword and suggesting related software ideas,

[0800] A means of providing the user with a summary of the proposed software idea and its implementation method,

[0801] A system that includes this.

[0802] (Claim 2)

[0803] The system according to claim 1, wherein data collection from the open-source platform is performed automatically.

[0804] (Claim 3)

[0805] The system according to claim 1, wherein the generated software ideas are filtered based on the user's preferences.

[0806] "Example 1"

[0807] (Claim 1)

[0808] Means of collecting information from an information sharing platform,

[0809] A means for analyzing the program description of the information and generating summary information,

[0810] Means for storing the summary information in a storage device,

[0811] A means for extracting relevant terms from social issues entered by the operator,

[0812] A means for searching for storage devices using the said term and proposing related concepts,

[0813] A means of providing the operator with a summary of the proposed concept and its implementation method,

[0814] A system that includes this.

[0815] (Claim 2)

[0816] The system according to claim 1, wherein data collection from the information sharing platform is performed automatically.

[0817] (Claim 3)

[0818] The system according to claim 1, wherein the generated concepts are selected based on the operator's preferences.

[0819] "Application Example 1"

[0820] (Claim 1)

[0821] A means of obtaining program information from an open-source technology sharing platform,

[0822] A means for analyzing the source code of the program information and generating summary information,

[0823] Means for storing the summary information in an information management device,

[0824] A method for extracting relevant keywords from social issues entered by users,

[0825] A means of searching for information management devices using the relevant keywords and proposing related technical ideas,

[0826] A means of providing users with a summary of the proposed technical idea and its implementation method,

[0827] A means of presenting solutions to problems related to urban functions,

[0828] A system that includes this.

[0829] (Claim 2)

[0830] The system according to claim 1, wherein data acquisition from the open-source technology sharing platform is performed automatically.

[0831] (Claim 3)

[0832] The system according to claim 1, wherein the generated technical ideas are selected based on the user's preferences.

[0833] "Example 2 of combining an emotion engine"

[0834] (Claim 1)

[0835] A means of collecting program information from an information sharing platform,

[0836] A means for analyzing the set of instructions in the program information and generating summary information,

[0837] Means for storing the summary information in a storage device,

[0838] A means of extracting relevant characteristic words from social issues entered by users,

[0839] A means for searching for a storage device using the characteristic word and proposing a related program design,

[0840] A means for analyzing the user's emotional state using an emotion recognition function and adjusting suggestions based on that state,

[0841] A means of providing users with a summary of the proposed program design and its implementation method,

[0842] A system that includes this.

[0843] (Claim 2)

[0844] The system according to claim 1, wherein data collection from the information sharing platform is performed automatically.

[0845] (Claim 3)

[0846] The system according to claim 1, wherein the generated program designs are filtered based on the user's preferences.

[0847] "Application example 2 when combining with an emotional engine"

[0848] (Claim 1)

[0849] Means of collecting information from open platforms,

[0850] A means for analyzing the data of the software information and generating summary information,

[0851] Means for storing the summary information,

[0852] A means of extracting relevant words from the tasks entered by the user,

[0853] A means of searching for stored information using the relevant term and proposing related ideas,

[0854] A means for providing a summary of the proposed idea and its implementation method,

[0855] A means of analyzing emotions and adjusting the content of proposals,

[0856] Based on the emotions and challenges, a means of proposing life support resources,

[0857] A system that includes this.

[0858] (Claim 2)

[0859] The system according to claim 1, wherein information collection from the platform is performed automatically.

[0860] (Claim 3)

[0861] The system according to claim 1, wherein the generated ideas are filtered based on the user's preferences. [Explanation of Symbols]

[0862] 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 software information from open-source platforms, A means for analyzing the source code of the software information and generating summary data, Means for storing the summary data in a database, A method for extracting relevant keywords from social issues entered by users, A means of searching a database using the keyword and suggesting related software ideas, A means of providing the user with a summary of the proposed software idea and its implementation method, A system that includes this.

2. The system according to claim 1, wherein data collection from the open-source platform is performed automatically.

3. The system according to claim 1, wherein the generated software ideas are filtered based on the user's preferences.

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