Learning context-free grammars from structural data in polynomial time

研究成果: Article査読

93 被引用数 (Scopus)

抄録

We consider the problem of learning a context-free grammar from its structural descriptions. Structural descriptions of a context-free grammar are unlabelled derivation trees of the grammar. We present an efficient algorithm for learning context-free grammars using two types of queries: structural equivalence queries and structural membership queries. The learning protocol is based on what is called "minimally adequate teacher", and it is shown that a grammar learned by the algorithm is not only a correct grammar, i.e. equivalent to the unknown grammar but also structurally equivalent to it. Furthermore, the algorithm runs in time polynomial in the number of states of the minimum frontier-to-root tree automaton for the set of structural descriptions of the unknown grammar and the maximum size of any counter-example returned by a structural equivalence query.

本文言語English
ページ(範囲)223-242
ページ数20
ジャーナルTheoretical Computer Science
76
2-3
DOI
出版ステータスPublished - 1990 11月 21
外部発表はい

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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