Performance Evaluation of Semantic Reasoners

As the performance of semantic reasoners change significantly with regard to all included characteristics, and therefore requires assessment and evaluation before selecting an appropriate reasoner for a given application. There are number of inference engines like Pellet, FaCT++, Hermit, RacerPro, KaON2, F-OWL and BaseVISor. Some of them are reviewed and tested for few prebuilt ontologies. Paper presents a performance evaluation and comparison of semantic reasoner for ontology of Health and Anatomy domain. Reasoners are characterized based on reasoning method, reasoning algorithm, computational complexity, classification, scalability, query and rule support. KeywordsOWL, Inference Engine, Semantic reasoner.