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.



More About This Work

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