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. © 2011 Springer-Verlag Berlin Heidelberg.
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CITATION STYLE
Yoshinaka, R., & Kanazawa, M. (2011). Distributional learning of abstract categorial grammars. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6736 LNAI, pp. 251–266). https://doi.org/10.1007/978-3-642-22221-4_17
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