• DocumentCode
    680733
  • Title

    A Novel Combination of Reasoners for Ontology Classification

  • Author

    Changlong Wang ; Zhiyong Feng

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Tianjin Univ., Tianjin, China
  • fYear
    2013
  • fDate
    4-6 Nov. 2013
  • Firstpage
    463
  • Lastpage
    468
  • Abstract
    Large scale ontology applications require efficient reasoning services, of which ontology classification is the fundamental reasoning task. The special EL reasoners are efficient, but they can not classify ontologies with axioms outside the OWL 2 EL profile. The general-purpose OWL 2 reasoners for expressive Description Logics are less efficient when classifying the OWL 2 EL ontologies. In this work, we propose a novel technique that combines an OWL 2 reasoner with an EL reasoner for classification of ontologies expressed in DL SROIQ. We develop an efficient task decomposition algorithm for identifying the minimal non-EL module that is assigned to the OWL 2 reasoner, and the bulk of the workload is assigned to the EL reasoner. Furthermore, this paper reports on the implementation of our approach in the ComR system which integrates the two types of reasoners in a black-box manner. The experimental results show that our method leads to a reasonable task assignment and can offer a substantial speed up (over 50%) in ontology classification.
  • Keywords
    ontologies (artificial intelligence); pattern classification; ComR system; OWL 2 EL profile; description logics; large scale ontology applications; ontology classification; reasoning services; Classification algorithms; Cognition; OWL; Ontologies; Optimization; Proteins; Semantics; OWL 2; OWL 2 EL; combination; description logic; ontology classification; reasoner;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Tools with Artificial Intelligence (ICTAI), 2013 IEEE 25th International Conference on
  • Conference_Location
    Herndon, VA
  • ISSN
    1082-3409
  • Print_ISBN
    978-1-4799-2971-9
  • Type

    conf

  • DOI
    10.1109/ICTAI.2013.75
  • Filename
    6735286