Pellet: A practical OWL-DL reasoner
Web Semantics: Science, Services and Agents on the World Wide Web
Consequence-driven reasoning for horn SHIQ ontologies
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
The Description Logic Handbook: Theory, Implementation and Applications
The Description Logic Handbook: Theory, Implementation and Applications
Optimized description logic reasoning via core blocking
IJCAR'10 Proceedings of the 5th international conference on Automated Reasoning
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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.