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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Towards Dual Approaches for Learning Context-Free Grammars Based on Syntactic Concept Lattices
verfasst von : Ryo Yoshinaka
Erschienen in: Developments in Language Theory
Verlag: Springer Berlin Heidelberg
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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.