Distributional learning of abstract categorial grammars

Ryo Yoshinaka, Makoto Kanazawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationLogical Aspects of Computational Linguistics - 6th International Conference, LACL 2011, Proceedings
Pages251-266
Number of pages16
DOIs
Publication statusPublished - 2011 Jul 14
Externally publishedYes
Event6th International Conference on Logical Aspects of Computational Linguistics, LACL 2011 - Montpellier, France
Duration: 2011 Jun 292011 Jul 1

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6736 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference on Logical Aspects of Computational Linguistics, LACL 2011
CountryFrance
CityMontpellier
Period11/6/2911/7/1

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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