An Abduction-Based Method for Index Relaxation in Taxonomy-Based Sources

  • Carlo Meghini
  • Yannis Tzitzikas
  • Nicolas Spyratos
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2747)

Abstract

The extraction of information from a source containing term-classified objects is plagued with uncertainty. In the present paper we deal with this uncertainty in a qualitative way. We view an information source as an agent, operating according to an open world philosophy. The agent knows some facts, but is aware that there could be other facts, compatible with the known ones, that might hold as well, although they are not captured for lack of knowledge. These facts are, indeed, possibilities. We view possibilities as explanations and resort to abduction in order to define precisely the possibilities that we want our system to be able to handle. We introduce an operation that extends a taxonomy-based source with possibilities, and then study the property of this operation from a mathematical point of view.

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References

  1. 1.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. ACM Press, Addison-Wesley (1999)Google Scholar
  2. 2.
    Boolos, G.: Logic, Logic and Logic. Harvard University Press, Cambridge (1998)MATHGoogle Scholar
  3. 3.
    Donini, F.M., Lenzerini, M., Nardi, D., Schaerf, A.: Reasoning in description logics. In: Brewka, G. (ed.) Principles of Knowledge Representation. Studies in Logic, Language and Information, pp. 193–238. CSLI Publications, Stanford (1996)Google Scholar
  4. 4.
    Eiter, T., Gottlob, G.: The complexity of logic-based abduction. Journal of the ACM 42(1), 3–42 (1995)MATHCrossRefMathSciNetGoogle Scholar
  5. 5.
    Enderton, H.B.: A mathematical introduction to logic. Academic Press, N.Y. (1972)MATHGoogle Scholar
  6. 6.
    Fejer, P.A., Simovici, D.A.: Mathematical Foundations of Computer Science. Sets, Relations, and Induction, vol. 1. Springer, Heidelberg (1991)MATHGoogle Scholar
  7. 7.
    Papadimitriou, C.H.: Computational complexity. Addison-Wesley, Reading (1994)MATHGoogle Scholar
  8. 8.
    Sacco, G.M.: Dynamic Taxonomies: A Model for Large Information Bases. IEEE Transactions on Knowledge and Data Engineering 12(3) (May 2000)Google Scholar
  9. 9.
    Tzitzikas, Y., Analyti, A., Spyratos, N., Constantopoulos, P.: An Algebra for Specifying Compound Terms for Faceted Taxonomies. In: Kitakyushu, J. (ed.) 13th European-Japanese Conf. on Information Modelling and Knowledge Bases (June 2003)Google Scholar
  10. 10.
    Zunde, P., Dexter, M.E.: Indexing Consistency and Quality. American Documentation 20(3), 259–267 (1969)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Carlo Meghini
    • 1
  • Yannis Tzitzikas
    • 1
  • Nicolas Spyratos
    • 2
  1. 1.Consiglio Nazionale delle RicercheIstituto della Scienza e delle Tecnologie della InformazionePisaItaly
  2. 2.Laboratoire de Recherche en InformatiqueUniversite de Paris-SudFrance

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