Distributional Learning of Simple Context-Free Tree Grammars

  • Anna Kasprzik
  • Ryo Yoshinaka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6925)

Abstract

This paper demonstrates how existing distributional learning techniques for context-free grammars can be adapted to simple context-free tree grammars in a straightforward manner once the necessary notions and properties for string languages have been redefined for trees. Distributional learning is based on the decomposition of an object into a substructure and the remaining structure, and on their interrelations. A corresponding learning algorithm can emulate those relations in order to determine a correct grammar for the target language.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Anna Kasprzik
    • 1
  • Ryo Yoshinaka
    • 2
  1. 1.FB IV InformatikUniversity of TrierTrier
  2. 2.ERATO MINATO ProjectJapan Science and Technology AgencyJapan

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