Approximating linear order inference in OWL 2 DL by horn compilation

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings - 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012
Pages97-104
Number of pages8
DOIs
Publication statusPublished - 1 Dec 2012
Event2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012 - Macau, China
Duration: 4 Dec 20127 Dec 2012

Conference

Conference2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012
CountryChina
CityMacau
Period4/12/127/12/12

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Keywords

  • description logics
  • inconsistency handling
  • knowledge compilation
  • linear order inference
  • OWL 2 DL

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

Cite this

Du, J., Qi, G., Pan, J. Z., & Shen, Y. D. (2012). Approximating linear order inference in OWL 2 DL by horn compilation. In Proceedings - 2012 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2012 (pp. 97-104). [6511871] https://doi.org/10.1109/WI-IAT.2012.11