Distributional learning of simple context-free tree grammars

Anna Kasprzik, Ryo Yoshinaka

研究成果: Conference contribution

15 被引用数 (Scopus)

抄録

This paper demonstrates how existing distributional learning techniques for context-free grammars can be adapted to simple context-free tree grammars in a straightforward manner once the necessary notions and properties for string languages have been redefined for trees. Distributional learning is based on the decomposition of an object into a substructure and the remaining structure, and on their interrelations. A corresponding learning algorithm can emulate those relations in order to determine a correct grammar for the target language.

本文言語English
ホスト出版物のタイトルAlgorithmic Learning Theory - 22nd International Conference, ALT 2011, Proceedings
ページ398-412
ページ数15
DOI
出版ステータスPublished - 2011 10 20
外部発表はい
イベント22nd International Conference on Algorithmic Learning Theory, ALT 2011 - Espoo, Finland
継続期間: 2011 10 52011 10 7

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)
6925 LNAI
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Other

Other22nd International Conference on Algorithmic Learning Theory, ALT 2011
国/地域Finland
CityEspoo
Period11/10/511/10/7

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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