Hierarchical Knowledge Graphs and their Application

Abstract

The transformation of the world's knowledge from poorly structured texts, to well-structured knowledge graphs (KG) is a common practice. KGs are well-suited for AI applications, but their human representation can pose challenges for clarity and navigation, especially when dealing with a large number of elements. To address the issue, we propose the introduction of a new type of diagram known as the Hierarchical Knowledge Graph (HKG). Based on the models of cognitive psychology, the HKG has the potential to enhance the use of KGs and ontologies in educational contexts, as it can serve as presentable lecture notes and an alternative to traditional textbooks. This article presents a novel prototype of an application.