Leveraging Large Language Models for Semantic Query Processing in a Scholarly Knowledge Graph
This paper proposes a novel framework that integrates Large Language Models with the Australian National University's Computer Science Scholarly Knowledge Graph, utilizing a Deep Document Model and KG-enhanced Query Processing to enable accurate, fine-grained semantic retrieval of research artifacts through automatic LLM-SPARQL fusion.