Distributional Learning of Abstract Categorial Grammars

  • Ryo Yoshinaka
  • Makoto Kanazawa
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6736)

Abstract

Recent studies on grammatical inference have demonstrated the benefits of the learning strategy called “distributional learning” for context-free and multiple context-free languages. This paper gives a comprehensive view of distributional learning of “context-free” formalisms (roughly in the sense of Courcelle 1987) in terms of abstract categorial grammars, in which existing “context-free” formalisms can be encoded.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ryo Yoshinaka
    • 1
  • Makoto Kanazawa
    • 2
  1. 1.ERATO MINATO Discrete Structure Manipulation System ProjectJapan Science and Technology AgencyJapan
  2. 2.National Institute of InformaticsJapan

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