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Hitting the Sweetspot: Economic Rewriting of Knowledge Bases

  • Nadeschda Nikitina
  • Birte Glimm
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7649)

Abstract

Three conflicting requirements arise in the context of knowledge base (KB) extraction: the size of the extracted KB, the size of the corresponding signature and the syntactic similarity of the extracted KB with the original one. Minimal module extraction and uniform interpolation assign an absolute priority to one of these requirements, thereby limiting the possibilities to influence the other two. We propose a novel technique for \({\mathcal EL}\) that does not require such an extreme prioritization. We propose a tractable rewriting approach and empirically compare the technique with existing approaches with encouraging results.

Keywords

Knowledge Base General Module Relation Pair Atomic Concept Minimal Module 
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.

References

  1. 1.
    Cuenca Grau, B., Horrocks, I., Kazakov, Y., Sattler, U.: Just the right amount: extracting modules from ontologies. In: Proc. of the 16th Int. Conf. on World Wide Web (WWW 2007), pp. 717–726 (2007)Google Scholar
  2. 2.
    Konev, B., Walther, D., Wolter, F.: Forgetting and uniform interpolation in large-scale description logic terminologies. In: Proc. of the 21st Int. Joint Conf. on Artificial Intelligence (IJCAI 2009), pp. 830–835 (2009)Google Scholar
  3. 3.
    Kontchakov, R., Wolter, F., Zakharyaschev, M.: Logic-based ontology comparison and module extraction, with an application to DL-Lite. Artificial Intelligence 174, 1093–1141 (2010)MathSciNetzbMATHCrossRefGoogle Scholar
  4. 4.
    Lutz, C., Wolter, F.: Foundations for uniform interpolation and forgetting in expressive description logics. In: Proc. of the 22nd Int. Joint Conf. on Artificial Intelligence (IJCAI 2011), pp. 989–995 (2011)Google Scholar
  5. 5.
    Motik, B., Cuenca Grau, B., Horrocks, I., Wu, Z., Fokoue, A., Lutz, C. (eds.): OWL 2 Web Ontology Language: Profiles. W3C Recommendation (October 27, 2009), http://www.w3.org/TR/owl2-profiles/
  6. 6.
    Nikitina, N., Glimm, B.: Hitting the sweetspot: Economic rewriting of knowledge bases. Techreport, AIFB, KIT, Karlsruhe (May 2012)Google Scholar
  7. 7.
    Nikitina, N., Rudolph, S.: ExpExpExplosion: Uniform interpolation in general EL terminologies. In: Proc. of the 20th European Conf. on Artificial Intelligence, ECAI 2012 (2012)Google Scholar
  8. 8.
    Nikitina, N., Rudolph, S., Glimm, B.: Reasoning-supported interactive revision of knowledge bases. In: Proc. of the 22nd Int. Joint Conf. on Artificial Intelligence (IJCAI 2011), pp. 1027–1032 (2011)Google Scholar
  9. 9.
    OWL Working Group, W.: OWL 2 Web Ontology Language: Document Overview. W3C Recommendation (October 27, 2009), http://www.w3.org/TR/owl2-overview/

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Nadeschda Nikitina
    • 1
  • Birte Glimm
    • 2
  1. 1.Institute AIFBKarlsruhe Institute of TechnologyGermany
  2. 2.Institute of Artificial IntelligenceUniversity of UlmGermany

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