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Automatic Extraction of Semantic Relationships for WordNet by Means of Pattern Learning from Wikipedia

  • Maria Ruiz-Casado
  • Enrique Alfonseca
  • Pablo Castells
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3513)

Abstract

This paper describes an automatic approach to identify lexical patterns which represent semantic relationships between concepts, from an on-line encyclopedia. Next, these patterns can be applied to extend existing ontologies or semantic networks with new relations. The experiments have been performed with the Simple English Wikipedia and WordNet 1.7. A new algorithm has been devised for automatically generalising the lexical patterns found in the encyclopedia entries. We have found general patterns for the hyperonymy, hyponymy, holonymy and meronymy relations and, using them, we have extracted more than 1200 new relationships that did not appear in WordNet originally. The precision of these relationships ranges between 0.61 and 0.69, depending on the relation.

Keywords

Edit Distance Semantic Network Semantic Relationship Automatic Extraction Empty String 
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 2005

Authors and Affiliations

  • Maria Ruiz-Casado
    • 1
  • Enrique Alfonseca
    • 1
  • Pablo Castells
    • 1
  1. 1.Computer Science DepUniversidad Autonoma de MadridMadridSpain

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