On the analysis of fuzzy string patterns with the help of extended and stochastic GDPLL(k) grammars

Authors:
Mariusz Flasiński;Janusz Jurek
Affiliations:
Institute of Computer Science, Jagiellonian University, Cracow, Poland;Institute of Computer Science, Jagiellonian University, Cracow, Poland
Venue:
Fundamenta Informaticae - Special issue on theory and applications of soft computing (TASC04)
Year:
2006

Citing 4
Cited 2

Distorted pattern analysis with the help of node label controlled graph languages

Pattern Recognition
Syntax-Directed Transduction

Journal of the ACM (JACM)
Programmed Grammars and Classes of Formal Languages

Journal of the ACM (JACM)
On the linear computational complexity of the parser for quasi-context sensitive languages

Pattern Recognition Letters

Inference of Parsable Graph Grammars for Syntactic Pattern Recognition

Fundamenta Informaticae
Inference of Parsable Graph Grammars for Syntactic Pattern Recognition

Fundamenta Informaticae

Quantified Score

Hi-index	0.00

Visualization

Abstract

Two methods of the analysis of distorted (fuzzy) string patterns are presented. The methods are based on the use of GDPLL(k) grammars generating a large subclass of context sensitive languages. The first one utilizes error-correcting approach: a minimum distance measure is used for error-correcting parsing. The second one utilizes stochastic approach: the decision about the production to be applied in a derivation step is given according to the probability measure.