Optimising Ontology Classification

  • Birte Glimm
  • Ian Horrocks
  • Boris Motik
  • Giorgos Stoilos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6496)


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.


Data Property Object Property Object Domain Property Chain Property Hierarchy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Birte Glimm
    • 1
  • Ian Horrocks
    • 1
  • Boris Motik
    • 1
  • Giorgos Stoilos
    • 1
  1. 1.Computing LaboratoryOxford UniversityUK

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