Optimising ontology classification

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Abstract

Ontology classification - the computation of subsumption hierarchies for classes and properties - is one of the most important tasks for OWL reasoners. Based on the algorithm by Shearer and Horrocks [9], we present a new classification procedure that addresses several open issues of the original algorithm, and that uses several novel optimisations in order to achieve superior performance. We also consider the classification of (object and data) properties. We show that algorithms commonly used to implement that task are incomplete even for relatively weak ontology languages. Furthermore, we show how to reduce the property classification problem into a standard (class) classification problem, which allows reasoners to classify properties using our optimised procedure. We have implemented our algorithms in the OWL HermiT reasoner, and we present the results of a performance evaluation. © 2010 Springer-Verlag.

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APA

Glimm, B., Horrocks, I., Motik, B., & Stoilos, G. (2010). Optimising ontology classification. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6496 LNCS, pp. 225–240). Springer Verlag. https://doi.org/10.1007/978-3-642-17746-0_15

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