KR-20260062138-A - A research support method using a researcher community platform equipped with LLM-based research assistance AI

KR20260062138AKR 20260062138 AKR20260062138 AKR 20260062138AKR-20260062138-A

Abstract

The “research support method by a researcher community platform equipped with an LLM-based research assistance AI” according to the present invention is composed of the following process. A user terminal (20) logs into an intermediary (10), which is a server equipped with LLM-based AI, and a main screen access step is performed in which the intermediary (10) outputs a menu tab (65) for research plan creation, chatbot chat, expert matching, online lecture, data analysis, and community forum on the display of the user terminal (20). After the above main screen access step, the user terminal (20) clicks on one of the menu tabs (65) to receive services for research plan creation, chatbot chatting, expert matching, online lectures, data analysis, and community forums. Therefore, the following effects are achieved. Graduate students or researchers at general companies can receive guidance and advice on the direction of research proposals and thesis writing through AI, while simultaneously receiving assistance from experts in the relevant field to address any shortcomings. In reality, it is generally difficult to receive consulting from figures who are hard to approach, such as academic advisors or senior researchers at research institutes. However, according to this invention, it is possible to receive consulting from top authorities in the relevant field. In addition, it has the effect of providing a process that allows users to selectively take online courses to acquire the knowledge necessary for writing papers, and efficiently offers data analysis and community forums. In addition, the aforementioned expert matching and online courses have a beneficial effect on users because they can lower fees through mutual competition. In addition, users who access the site of the present invention pay membership fees upon registration and naturally access expert matching and online courses, thereby generating revenue; thus, it has the effect of reducing analysis costs compared to other sites that specialize solely in analysis.

Inventors

김길재
박강윤

Assignees

김길재
박강윤

Dates

Publication Date: 20260507
Application Date: 20241025

Claims (5)

An intermediary, which is a server computer equipped with LLM (Large Language Models)-based AI (Artificial Intelligence), has a database built, is capable of data analysis, and enables chatbot chatting, and A user terminal capable of communicating with the above-mentioned intermediary via the Internet network, and A professional terminal capable of communicating with the above-mentioned intermediary via the Internet network, and The above-mentioned intermediary includes an online course server capable of communicating via the Internet network, and In a system in which the above-mentioned intermediary outputs a main screen on the display of the above-mentioned user terminal and presents research plan creation, chatbot chatting, expert matching, online lectures, data analysis, and a community forum as clickable menu tabs on the main screen, A main screen access step in which the user terminal logs into the intermediary and the intermediary outputs the menu tab on the display of the user terminal, and After the above main screen access step, the process includes the user terminal clicking on any one of the above menu tabs to receive services for research plan creation, chatbot chatting, expert matching, online lectures, data analysis, and community forums. After the main screen access step described above, a research plan selection step in which the user terminal clicks the research plan creation menu tab, and After the research plan selection step above, the user terminal receives and outputs an input form from the intermediary, and the user terminal inputs research information into the input form in an input form creation step, and After the above input form creation step, the above intermediary provides the research plan to the above user terminal in the form of a report in an output step, and After the main screen access step described above, a chatbot selection step in which the user terminal selects the chatbot chat menu tab, and After the chatbot selection step described above, the method includes a chat step in which the user terminal chats with the intermediary and the chatbot. After the chatting step above, an expert matching selection step in which the user terminal clicks the expert matching menu tab, and After the expert matching selection step described above, the user terminal receives an input form from the intermediary, and the user terminal inputs the content it wishes to receive consulting into the input form in an input form creation step, and After the above input form completion step, an expert recommendation step in which the above intermediary searches for an expert corresponding to the above consulting content and transmits them to the above user terminal, and After the above expert recommendation step, an expert selection step in which the user terminal approves the expert, and After the above expert selection step, a payment step in which the above user terminal makes a payment, and After the above payment step, the intermediary sends the contact information of the user terminal to the expert terminal, and includes a consulting step in which the user terminal and the expert terminal communicate with each other. A research support method by a researcher community platform equipped with an LLM-based research assistant AI, characterized in that, after the expert selection step, if the user terminal does not make a payment, the intermediary terminates the process.
In paragraph 1, After the above main screen access step, an online course selection step in which the user terminal clicks the online course menu tab, and After the above online course selection step, the above intermediary sends an input form to the above user terminal, and the above user terminal enters the content it wishes to take into the input form in an input form creation step, and After the above input form completion step, a course recommendation step in which the above intermediary searches for the course the user wishes to take and sends a course introduction to the above user terminal, and After the course recommendation step above, a course selection step in which the user terminal approves the course, and After the above course selection step, a payment step in which the above user terminal makes a payment, and After the above payment step, the above intermediary enables the user terminal to connect to the above online course server and includes a course taking step in which the user terminal receives the above online course. A research support method by a researcher community platform equipped with an LLM-based research assistant AI, characterized in that, after the course selection step, if the user terminal does not make a payment, the intermediary terminates the process.
In paragraph 1 or 2, After the main screen access step described above, a data analysis selection step in which the user terminal clicks the data analysis menu tab, and After the above data analysis selection step, an upload step in which the user terminal transmits the data to be analyzed to the intermediary, and After the above upload step, a payment step in which the user terminal makes a payment, and After the above payment step, the method includes an output step in which the intermediary transmits analysis data to the user terminal, and A research support method by a researcher community platform equipped with an LLM-based research assistance AI, characterized by including a process in which, after the upload step, if the user terminal does not make a payment, the intermediary terminates the process.
In paragraph 3, After the above main screen access step, a community forum selection step in which the user terminal selects the community forum menu tab, and After the community forum selection step above, a posting step in which the user terminal transmits a discussion topic to the mediator and the mediator posts the discussion topic to other user terminals and expert terminals, and A research support method by a researcher community platform equipped with an LLM-based research assistance AI, characterized in that, after the above-mentioned posting step, the mediator includes a communication step that enables the user terminal, other user terminals, and expert terminals to communicate with each other like SNS.
In paragraph 1 or 2, After the consulting step described above, the method includes an evaluation step in which the user terminal transmits the score of the expert who provided consulting to the intermediary, and The above-mentioned intermediary includes a process of determining whether to expel the above-mentioned expert by settling the expert's evaluation score over a prescribed period, and After the above course taking stage, the evaluation stage is included in which the user terminal sends the score of the online course provided to the intermediary. A research support method by a researcher community platform equipped with an LLM-based research assistance AI, characterized in that the above-mentioned intermediary includes a process of determining whether to expel the above-mentioned online course by settling the evaluation scores of the above-mentioned online course over a prescribed period.

Description

A research support method using a researcher community platform equipped with LLM-based research assistance AI The present invention relates to a "method for supporting research by a researcher community platform equipped with an LLM-based research assistance AI," and more specifically, to a "method for supporting research by a researcher community platform equipped with an LLM-based research assistance AI" characterized by a process that can efficiently support a researcher's research by supporting artificial intelligence, expert consulting, online lectures, data analysis, and community forums. Artificial Intelligence (AI) is a computer system capable of performing functions of human intelligence, such as learning, reasoning, adaptation, and argumentation. Among these, Large Language Models (LLMs) are a type of AI that is a program capable of analyzing various types of textual information. The aforementioned LLM is an AI model capable of recognizing and generating text by learning from large-scale data; as its name suggests, it learns based on vast datasets. In particular, LLM operates based on neural networks known as Transformer models within machine learning techniques. Generally, it has long been common knowledge to utilize such AI assistance when writing academic papers. Prior art literature presents a process for writing papers using the aforementioned AI. Specifically, the AI provides the references requested by the author, and when the author extracts and includes parts of the references in the paper during writing, the AI acts as a server for a writing system that collects information related to those references along with the written paper, thereby facilitating the writing of the paper through the writing system. According to this background technology, there were the following problems. Graduate students and researchers at general companies face significant difficulties in writing theses due to pressure to produce high results, the lack of readily available research information, and high costs for analysis and consulting. In particular, it is true that most university academic advisors are indifferent to these struggles and are authoritarian, making it difficult for students to approach them. Consequently, academic advisors are failing to properly fulfill their role as consultants. Of course, AI-based paper writing systems have been proposed, as seen in the prior art literature, but these merely provide references and could not fundamentally solve the difficulties mentioned above. FIG. 1 is a simplified diagram illustrating a system that enables the process of the present invention. FIG. 2 is a flowchart illustrating a research support method by a researcher community platform equipped with an LLM-based research assistance AI according to the present invention. FIG. 3 is an example diagram illustrating the state in which the main screen is displayed during the main screen access step after the login step in the present invention. Figure 4 is an example diagram illustrating an input form displayed in the input form creation step after the research plan selection step in the present invention. Hereinafter, various embodiments of this document are described with reference to the accompanying drawings. However, this is not intended to limit the technology described in this document to specific embodiments and should be understood to include various modifications, equivalents, and/or alternatives to the embodiments of this document. In relation to the description of the drawings, similar reference numerals may be used for similar components. Furthermore, expressions such as "First," "Second," etc., used in this document may modify various components regardless of order and/or importance, and are used merely to distinguish one component from another without limiting such components. For example, "Part 1" and "Part 2" may refer to different parts regardless of order or importance. For instance, without departing from the scope of rights described in this document, Part 1 may be named Part 2, and similarly, Part 2 may be renamed Part 1. Furthermore, the terms used in this document are used merely to describe specific embodiments and are not intended to limit the scope of other embodiments. Singular expressions may include plural expressions unless the context clearly indicates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as generally understood by those skilled in the art described in this document. Terms used in this document that are defined in general dictionaries may be interpreted as having the same or similar meaning as they have in the context of the relevant technology, and are not to be interpreted in an ideal or overly formal sense unless explicitly defined in this document. In some cases, even terms defined in this document may not be interpreted to exclude the embodiments of this document. Hereinafter, detailed embodiments of the "research