• DocumentCode
    2118036
  • Title

    Approximating Linear Order Inference in OWL 2 DL by Horn Compilation

  • Author

    Jianfeng Du ; Guilin Qi ; Pan, Jeff Z. ; Yi-Dong Shen

  • Author_Institution
    Guangdong Univ. of Foreign Studies, Guangzhou, China
  • Volume
    1
  • fYear
    2012
  • fDate
    4-7 Dec. 2012
  • Firstpage
    97
  • Lastpage
    104
  • Abstract
    In order to directly reason over inconsistent OWL 2 DL ontologies, this paper considers linear order inference which comes from propositional logic. Consequences of this inference in an inconsistent ontology are defined as consequences in a certain consistent sub-ontology. This paper proposes a novel framework for compiling an OWL 2 DL ontology to a Horn propositional program so that the intended consistent sub-ontology for linear order inference can be approximated from the compiled result in polynomial time. A tractable method is proposed to realize this framework. It guarantees that the compiled result has a polynomial size. Experimental results show that the proposed method computes the exact intended sub-ontology for almost all test cases, while it is significantly more efficient and scalable than state-of-the-art exact methods.
  • Keywords
    formal logic; inference mechanisms; knowledge representation languages; ontologies (artificial intelligence); Horn propositional program; OWL 2 DL ontologies; OWL 2 DL ontology; consistent subontology; horn compilation; inconsistent ontology; linear order inference; polynomial time; propositional logic; tractable method; OWL 2 DL; description logics; inconsistency handling; knowledge compilation; linear order inference;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Intelligence and Intelligent Agent Technology (WI-IAT), 2012 IEEE/WIC/ACM International Conferences on
  • Conference_Location
    Macau
  • Print_ISBN
    978-1-4673-6057-9
  • Type

    conf

  • DOI
    10.1109/WI-IAT.2012.11
  • Filename
    6511871