Quantitative structural information for inferring context free grammars with an extended Cocke-Younger-Kasami algorithm

Authors:
Ming-Heng Zhang
Affiliations:
School of Economics, Shanghai University of Finance and Economics, Lane 777, Guo-Ding Road, 200433 Shanghai, China
Venue:
Pattern Recognition Letters
Year:
2011

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Abstract

In this paper, we propose an approach to quantitative structural information for inferring context free grammars. First, we construct derivative capacity of nonterminal symbols in context free grammar, concomitant indicator and embedded dimensional number of strings in samples set, which are called as quantitative structural information; then, we rewrite Cocke-Younger-Kasami (CYK) algorithm for parsing in the form of the derivative set; third, we present the construction of new production rule and the descriptive procedure for inferring with an extended CYK algorithm by the quantitative structural information. Finally, we discuss the extended CYK algorithm for inferring context free grammars.