Guarded hybrid knowledge bases12

  • Authors:

  • Stijn Heymans;Jos De bruijn;Livia Predoiu;Cristina Feier;Davy Van niewenborgh

  • Affiliations:

  • Digital enterprise research institute, university of innsbruck, technikerstrasse 21a, innsbruck, austria (e-mail: stijn.heymans@deri.at);Faculty of computer science, free university of bozen-bolzano, i-39100 bozen-bolzano, italy (e-mail: debruijn@inf.unibz.it);Institute of computer science, university of mannheim, a5, 6 68159 mannheim, germany (e-mail: livia@informatik.uni-mannheim.de);Digital enterprise research institute, university of innsbruck, technikerstrasse 21a, innsbruck, austria (e-mail: cristina.feier@deri.at);Department of computer science, vrije universiteit brussel, vub, pleinlaan 2, b1050 brussels, belgium (e-mail: dvnieuwe@vub.ac.be)

  • Venue:
  • Theory and Practice of Logic Programming
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

Recently, there has been a lot of interest in the integration of Description Logics (DL) and rules on the Semantic Web. We define guarded hybrid knowledge bases (or g-hybrid knowledge bases) as knowledge bases that consist of a Description Logic knowledge base and a guarded logic program, similar to the $\mathcal{DL}$ + log knowledge bases from Rosati (In Proceedings of the 10th International Conference on Principles of Knowledge Representation and Reasoning, AAAI Press, Menlo Park, CA, 2006, pp. 68–78.). g-Hybrid knowledge bases enable an integration of Description Logics and Logic Programming where, unlike in other approaches, variables in the rules of a guarded program do not need to appear in positive non-DL atoms of the body, i.e., DL atoms can act as guards as well. Decidability of satisfiability checking of g-hybrid knowledge bases is shown for the particular DL $\mathcal{DLRO}^{\-{le}}$, which is close to OWL DL, by a reduction to guarded programs under the open answer set semantics. Moreover, we show 2-Exptime-completeness for satisfiability checking of such g-hybrid knowledge bases. Finally, we discuss advantages and disadvantages of our approach compared with $\mathcal{DL}$ + log knowledge bases.