Learning Mildly Context-Sensitive Languages with Multidimensional Substitutability from Positive Data

  • Ryo Yoshinaka
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5809)


Recently Clark and Eyraud (2007) have shown that substitutable context-free languages, which capture an aspect of natural language phenomena, are efficiently identifiable in the limit from positive data. Generalizing their work, this paper presents a polynomial-time learning algorithm for new subclasses of mildly context-sensitive languages with variants of substitutability.




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© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ryo Yoshinaka
    • 1
  1. 1.Graduate School of Information Science and TechnologyHokkaido UniversitySapporoJapan

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