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Parsing Preserving Techniques in Grammar Induction

Muresan, Smaranda

In this paper we present the theoretical foundation of the search space for learning a class of constraint-based grammars, which preserve the parsing of representative examples. We prove that under several assumptions the search space is a complete grammar lattice, and the lattice top element is a grammar that can always be learned from a set of representative examples and a sublanguage used to reduce the grammar semantics. This complete grammar lattice guarantees convergence of solutions of any learning algorithm that obeys the given assumptions.

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Academic Units
Computer Science
Publisher
Department of Computer Science, Columbia University
Series
Columbia University Computer Science Technical Reports, CUCS-032-05
Published Here
April 21, 2011
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