Model of syntactic recognition of distorted string patterns with the help of GDPLL(k)-based automata

doi:10.1007/978-3-319-00969-8_10

Model of syntactic recognition of distorted string patterns with the help of GDPLL(k)-based automata

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Model of syntactic recognition of distorted string patterns with the help of GDPLL(k)-based automata

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Bibliographic description

title:	Model of syntactic recognition of distorted string patterns with the help of GDPLL(k)-based automata
author:	Jurek Janusz , Peszek Tomasz
editor:	Burduk Robert, Jackowski Konrad, Kurzyński Marek, Woźniak Michał, Żołnierek Andrzej
book title:	Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013
volume:	1
date of publication :	2013
place of publication : name of publisher:	Cham ; New York : Springer
pages:	101-110
ISBN:	978-3-319-00968-1
eISBN:	978-3-319-00969-8
series:	Advances in Intelligent Systems and Computing, ISSN 2194-5357; eISSN 2194-5365; 226
DOI:	10.1007/978-3-319-00969-8_10
language:	English
book language:	English
abstract in English:	The process of syntactic pattern recognition consists of two main phases. In the first one the symbolic representation of a pattern is created (so called primitives are identified). In the second phase the representation is analyzed by a formal automaton on the base of a previously defined formal grammar (i.e. syntax analysis / parsing is performed). One of the main problems of syntactic pattern recognition is the analysis of distorted (fuzzy) patterns. If a pattern is distorted and the results of the first phase are wrong, then the second phase usually will not bring satisfactory results either. In this paper we present a model that could allow to solve the problem by involving an uncertainty factor (fuzziness/distortion) into the whole process of syntactic pattern recognition. The model is a hybrid one (based on artificial neural networks and GDPLL(k)-based automata) and it covers both phases of the recognition process (primitives’ identification and syntax analysis). We discuss the application area of this model, as well as the goals of further research.
number of pulisher's sheets:	1
conference:	8th International Conference on Computer Recognition Systems CORES 2013; 2013-05-27; 2013-05-29; Miłków; Polska; indeksowana w Web of Science; indeksowana w Scopus; ;
affiliation:	Wydział Zarządzania i Komunikacji Społecznej : Katedra Systemów Informatycznych
type:	chapter
subtype:	conference proceedings