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Learning (k,l)-Contextual Tree Languages for Information Extraction

  • Stefan Raeymaekers
  • Maurice Bruynooghe
  • Jan Van den Bussche
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3720)

Abstract

This paper introduces a novel method for learning a wrapper for extraction of text nodes from web pages based upon (k,l)-contextual tree languages. It also introduces a method to learn good values of k and l based on a few positive and negative examples. Finally, it describes how the algorithm can be integrated in a tool for information extraction.

Keywords

Information Extraction Target Node Tree Automaton Tree Language Tree Transducer 
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

  • Stefan Raeymaekers
    • 1
  • Maurice Bruynooghe
    • 1
  • Jan Van den Bussche
    • 2
  1. 1.Dept. of Computer ScienceK.U.LeuvenLeuven
  2. 2.Dept. Theoretical Computer ScienceUniversiteit HasseltDiepenbeek

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