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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.

Keywords

Information Source Description Logic Query Language Minimal Solution Propositional Variable 
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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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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