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Adaptive \(\mathcal{ALE}\)-TBox for Extending Terminological Knowledge

  • Ekaterina Ovchinnikova
  • Kai-Uwe Kühnberger
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4304)

Abstract

Ontologies are usually considered as static data structures representing conceptual knowledge of humans. For certain types of applications it would be desirable to develop an algorithmic adaptation process that allows dynamic modifications of the ontology in the case new information is available. Dynamic updates can generate conflicts between old and new information resulting in inconsistencies. We propose an algorithm that can model the adaptation processes for conflicting and non-conflicting updates defined on \(\mathcal{ALE}\)-TBoxes.

Keywords

Description Logic Concept Description Paraconsistent Logic Atomic Concept Ontological Knowledge 
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., Küsters, R.: Non-Standard Inferences in Description Logics: The Story So Far. In: Mathematical Problems from Applied Logic. New Logics for the XXIst Century. International Mathematical Series, vol. 4, pp. 1–75 (2006)Google Scholar
  2. 2.
    Baader, F., Lutz, C., Miličić, M., Sattler, U., Wolter, F.: Integrating Description Logics and Action Formalisms: First Results. In: Proc. of the 20th National Conference on Artificial Intelligence (AAAI 2005), pp. 572–577. AAAI Press, Menlo Park (2005)Google Scholar
  3. 3.
    Baader, F., Calvanese, D., McGuinness, D., Nardi, D., Patel-Schneider, P.: Description Logic Handbook: Theory, Implementation and Applications. Cambridge University Press, Cambridge (2003)MATHGoogle Scholar
  4. 4.
    Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web – A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities. Scientific American (2001)Google Scholar
  5. 5.
    Biemann, C., Shin, S., Choi, K.-S.: Semiautomatic Extension of CoreNet using a Bootstrapping Mechanism on Corpus-based Co-occurrences. In: Proc. of the 20th International Conference on Comp. Ling (Coling 2004), pp. 1227–1232 (2004)Google Scholar
  6. 6.
    Cohen, W., Hirsh, H.: Learning the CLASSIC Description Logic: Theoretical and Experimental Results. In: Proc. of the Fourth International Conference on Principles of Knowledge Representation and Reasoning (KR 1994), pp. 121–133 (1994)Google Scholar
  7. 7.
    Fanizzi, N., Ferilli, S., Iannone, L., Palmisano, I., Semeraro, G.: Downward Refinement in the ALN Description Logic. In: Proc. of the Fourth International Conference on Hybrid Intelligent Systems (HIS 2004), pp. 68–73 (2005)Google Scholar
  8. 8.
    Flouris, G., Plexousakis, D., Antoniou, G.: Updating Description Logics using the AGM Theory. In: Proc. the 7th International Symposium on Logical Formalizations of Commonsense Reasoning (2005)Google Scholar
  9. 9.
    Ghilardi, S., Lutz, C., Wolter, F.: Did I damage my ontology: A Case for Conservative Extensions of Description Logics. In: Proc. of Principles of Knowledge Representation and Reasoning (KR 2006) (to appear, 2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Ekaterina Ovchinnikova
    • 1
  • Kai-Uwe Kühnberger
    • 2
  1. 1.Seminar für SprachwissenschaftUniversity of Tübingen 
  2. 2.Institute of Cognitive ScienceUniversity of Osnabrück 

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