Ontology Summarization via Language Model

In the realm of knowledge representation, ontology serves as the backbone, enabling a shared and common understanding of a domain that can be communicated between people and systems. As the complexity and volume of ontologies grow, there arises a compelling need to summarize and distill this vast information. Enter the convergence of large language models and machine learning techniques, which offers an innovative avenue to efficiently abstract, interpret, and present ontology. This thesis delves into the exploration and application of these advanced large language models, such as ChatGPT in summarizing ontology, aiming to enhance accessibility and comprehension of domain-specific knowledge.