Hybrid reasoning for ontology classification

Abstract

Ontology classification is an essential reasoning task for ontology based systems. Tableau and resolution are two dominant types of reasoning procedures for ontology reasoning. Complex ontologies are often built on more expressive description logics and are usually highly cyclic. When reasoning complex ontologies, the both approaches may have difficulties in terms of reasoning results and performance, but for different ontology types. In this research, we investigate a hybrid reasoning approach, which will employ well-defined strategies to decompose and modify a complex ontology into subsets of ontologies based on capabilities of different reasoners, process the subsets with suitable individual reasoners, and combine such individual classification results into the overall classification result. The objective of our approach is to detect more subsumption relationships than individual reasoners for complex ontologies, and improve overall reasoning performance. © 2011 Springer-Verlag.