Jiaoyan Chen

Exploring Large Language Models in Ontology Reasoning and Construction

Abstract:

Ontology is widely used for knowledge representation in many domains like biomedicine and e-commerce, but ontology construction is always challenging, relying on a lot of manual costs and expertise. Ontology reasoning can support ontology construction and its application, but classic symbolic methods suffer from problems like the failure to deal with uncertainty, incompleteness and informally represented data. Although machine learning and neural-symbolic integration have been widely explored, the emergence of Large Language Models, especially its emergent capabilities in natural language understanding and generation, have attracted many researchers’ attention for advancing ontology reasoning and construction. In this talk, I will focus on language model-based ontology representation learning for ontology reasoning and generative large language models (LLMs) for complex proofs in OWL ontology, and briefly introduce some other works on LLMs for ontology alignment and completion.

Bio:

Dr. Jiaoyan Chen is Senior Lecturer (~Associate Professor) in Department of Computer Science, The University of Manchester. Before joining The University of Manchester in 2022, he worked as a Senior Researcher in University of Oxford since 2017 and got his PhD in Computer Science and Technology in Zhejiang University. Jiaoyan’s research focuses on Knowledge Graph, Ontology, and Artificial Intelligence. His publications has got ~6000 citations according to Google Scholar, and his recent research on Ontology Embedding was awarded an EPSRC New Investigator Award. Home page: https://chenjiaoyan.github.io/.