Towards dual approaches for learning context-free grammars based on syntactic concept lattices

研究成果: Conference contribution

23 被引用数 (Scopus)

抄録

Recent studies on grammatical inference have demonstrated the benefits of "distributional learning" for learning context-free and context-sensitive languages. Distributional learning models and exploits the relation between strings and contexts in the language of the learning target. There are two main approaches. One, which we call primal, constructs nonterminals whose language is characterized by strings. The other, which we call dual, uses contexts to characterize the language of a nonterminal of the conjecture grammar. This paper demonstrates and discusses the duality of those approaches by presenting some powerful learning algorithms along the way.

本文言語English
ホスト出版物のタイトルDevelopments in Language Theory - 15th International Conference, DLT 2011, Proceedings
ページ429-440
ページ数12
DOI
出版ステータスPublished - 2011
外部発表はい
イベント15th International Conference on Developments in Language Theory, DLT 2011 - Milan, Italy
継続期間: 2011 7 192011 7 22

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
6795 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other15th International Conference on Developments in Language Theory, DLT 2011
国/地域Italy
CityMilan
Period11/7/1911/7/22

ASJC Scopus subject areas

  • 理論的コンピュータサイエンス
  • コンピュータ サイエンス(全般)

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