Analysis of the Concept Learning Process Leading to Recovery Utilizing a Knowledge Graph-Based Chatbot

Yuka Enomoto, Neteru Masukawa, Atsushi Omata, Shogo Ishikawa

November 2023 Domestic Conference

Abstract

To support the acquisition of recovery concepts, we have developed a concept learning support system using a Knowledge Graph (KG) and the Large Language Model (LLM). With the increasing popularity of recovery concepts, there is a need for proper conceptual understanding, but the problem is that the quality of instructors is not guaranteed, resulting in misunderstanding of the concepts. In this study, we created a KG of the recovery concept and aimed to support the acquisition of appropriate concepts by providing learning support through an LLM-based chatbot that uses this information. Experimental results with university students suggest that KGs are useful for facilitating the understanding of concepts with clear definitions. On the other hand, in the case of concepts with a wide range of applications, it was suggested that the scale of KG needs to be expanded and its use needs to be improved.

Type

Conference paper

Publication

In The 61st SIGSWO":" Semantic Web and Ontology Workshop of the Japanese Society for Artificial Intelligence

LLM Knowledge Graph Chatbot