2011 | OriginalPaper | Chapter
Distributional Learning of Abstract Categorial Grammars
Authors : Ryo Yoshinaka, Makoto Kanazawa
Published in: Logical Aspects of Computational Linguistics
Publisher: Springer Berlin Heidelberg
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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.