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A Comparison of Reasoning Techniques for Querying Large Description Logic ABoxes

  • Boris Motik
  • Ulrike Sattler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4246)

Abstract

Many modern applications of description logics (DLs) require answering queries over large data quantities, structured according to relatively simple ontologies. For such applications, we conjectured that reusing ideas of deductive databases might improve scalability of DL systems. Hence, in our previous work, we developed an algorithm for reducing a DL knowledge base to a disjunctive datalog program. To test our conjecture, we implemented our algorithm in a new DL reasoner KAON2, which we describe in this paper. Furthermore, we created a comprehensive test suite and used it to conduct a performance evaluation. Our results show that, on knowledge bases with large ABoxes but with simple TBoxes, our technique indeed shows good performance; in contrast, on knowledge bases with large and complex TBoxes, existing techniques still perform better. This allowed us to gain important insights into strengths and weaknesses of both approaches.

Keywords

Theorem Prover Description Logic Conjunctive Query Deductive Database Query Answering 
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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References

  1. 1.
    Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P.F. (eds.): The Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, Cambridge (2003)MATHGoogle Scholar
  2. 2.
    Bachmair, L., Ganzinger, H., Lynch, C., Snyder, W.: Basic Paramodulation. Information and Computation 121(2), 172–192 (1995)MATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Bechhofer, S., Volz, R., Lord, P. W.: Cooking the Semantic Web with the OWL API. In: Fensel, D., Sycara, K.P., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 659–675. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  4. 4.
    Cumbo, C., Faber, W., Greco, G., Leone, N.: Enhancing the Magic-Set Method for Disjunctive Datalog Programs. In: Demoen, B., Lifschitz, V. (eds.) ICLP 2004. LNCS, vol. 3132, pp. 371–385. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  5. 5.
    Eiter, T., Faber, W., Leone, N., Pfeifer, G.: Declarative problem-solving using the DLV system. Logic-Based Artificial Intelligence 79–103 (2000)Google Scholar
  6. 6.
    Eiter, T., Leone, N., Mateis, C., Pfeifer, G., Scarcello, F.: A Deductive System for Non-Monotonic Reasoning. In: Fuhrbach, U., Dix, J., Nerode, A. (eds.) LPNMR 1997. LNCS (LNAI), vol. 1265, pp. 364–375. Springer, Heidelberg (1997)Google Scholar
  7. 7.
    Guo, Y., Pan, Z., Heflin, J.: An Evaluation of Knowledge Base Systems for Large OWL Datasets. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 274–288. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  8. 8.
    Haarslev, V., Möller, R.: RACER System Description. In: Goré, R.P., Leitsch, A., Nipkow, T. (eds.) IJCAR 2001. LNCS (LNAI), vol. 2083, pp. 701–706. Springer, Heidelberg (2001)CrossRefGoogle Scholar
  9. 9.
    Horrocks, I.: Optimising Tableaux Decision Procedures for Description Logics. PhD thesis, University of Manchester, UK (1997)Google Scholar
  10. 10.
    Horrocks, I., Patel-Schneider, P.F.: Reducing OWL entailment to description logic satisfiability. Journal of Web Semantics 1(4), 345–357 (2004)Google Scholar
  11. 11.
    Horrocks, I., Sattler, U., Tobies, S.: Practical Reasoning for Very Expressive Description Logics. Logic Journal of the IGPL 8(3), 239–263 (2000)MATHCrossRefMathSciNetGoogle Scholar
  12. 12.
    Hustadt, U., Motik, B., Sattler, U.: Reducing SHIQ Description Logic to Disjunctive Datalog Programs. In: Proc. KR 2004, Whistler, Canada, June 2–5, pp. 152–162. AAAI Press, Menlo Park (2004)Google Scholar
  13. 13.
    Hustadt, U., Motik, B., Sattler, U.: Data Complexity of Reasoning in Very Expressive Description Logics. In: Proc. IJCAI 2005, Edinburgh, UK, July 30–August 5, 2005, pp. 466–471. Morgan Kaufmann Publishers, San Francisco (2005)Google Scholar
  14. 14.
    McCune, W.W.: OTTER 3.0 Reference Manual and Guide. Technical Report ANL-94/6, Argonne National Laboratory (January 1994)Google Scholar
  15. 15.
    Motik, B.: Reasoning in Description Logics using Resolution and Deductive Databases. PhD thesis, Univesität Karlsruhe, Germany (2006)Google Scholar
  16. 16.
    Nieuwenhuis, R., Rubio, A.: Theorem Proving with Ordering and Equality Constrained Clauses. Journal of Symbolic Computation 19(4), 312–351 (1995)CrossRefMathSciNetGoogle Scholar
  17. 17.
    Parsia, B., Sirin, E.: Pellet: An OWL-DL Reasoner. Poster. In: Proc. ISWC 2004, Hiroshima, Japan, November 7–11 (2004)Google Scholar
  18. 18.
    Rector, A.L., Nowlan, W.A., Glowinski, A.: Goals for concept representation in the galen project. In: SCAMC 1993, Washington DC, USA, November 1-3, pp. 414–418. McGraw-Hill, New York (1993)Google Scholar
  19. 19.
    Riazanov, A., Voronkov, A.: The design and implementation of VAMPIRE. AI Communications 15(2–3), 91–110 (2002)MATHGoogle Scholar
  20. 20.
    Schulz, S.: E—A Brainiac Theorem Prover. AI Communications 15(2–3), 111–126 (2002)MATHGoogle Scholar
  21. 21.
    Schulz, S.: Simple and Efficient Clause Subsumption with Feature Vector Indexing. In: Proc. ESFOR, IJCAR 2004 Workshop, Cork, Ireland, July 4–8 (2004)Google Scholar
  22. 22.
    Tsarkov, D., Horrocks, I.: Ordering Heuristics for Description Logic Reasoning. In: Proc. IJCAI 2005, Edinburgh, UK, July 30 – August 5, pp. 609–614. Morgan Kaufmann Publishers, San Francisco (2005)Google Scholar
  23. 23.
    Volz, R.: Web Ontology Reasoning With Logic Databases. PhD thesis, Universität Fridericiana zu Karlsruhe (TH), Germany (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Boris Motik
    • 1
  • Ulrike Sattler
    • 1
  1. 1.University of ManchesterManchesterUK

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