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

Model of syntactic recognition of distorted string ...

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dc.contributor.author Jurek, Janusz [SAP11015096] pl
dc.contributor.author Peszek, Tomasz pl
dc.contributor.editor Burduk, Robert pl
dc.contributor.editor Jackowski, Konrad pl
dc.contributor.editor Kurzyński, Marek pl
dc.contributor.editor Woźniak, Michał pl
dc.contributor.editor Żołnierek, Andrzej pl
dc.date.accessioned 2014-09-23T10:56:10Z
dc.date.available 2014-09-23T10:56:10Z
dc.date.issued 2013 pl
dc.identifier.isbn 978-3-319-00968-1 pl
dc.identifier.uri http://ruj.uj.edu.pl/xmlui/handle/item/1140
dc.language eng pl
dc.title Model of syntactic recognition of distorted string patterns with the help of GDPLL(k)-based automata pl
dc.type BookSection pl
dc.pubinfo Cham ; New York : Springer pl
dc.description.physical 101-110 pl
dc.abstract.en 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. pl
dc.description.series Advances in Intelligent Systems and Computing, ISSN 2194-5357; eISSN 2194-5365; 226 pl
dc.description.volume 1 pl
dc.description.publication 1 pl
dc.description.conftype international pl
dc.identifier.doi 10.1007/978-3-319-00969-8_10 pl
dc.identifier.eisbn 978-3-319-00969-8 pl
dc.title.container Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013 pl
dc.language.container eng pl
dc.affiliation Wydział Zarządzania i Komunikacji Społecznej : Katedra Systemów Informatycznych pl
dc.subtype ConferenceProceedings pl
dc.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; ; pl
dc.rights.original OTHER; inne; ostateczna wersja wydawcy; po opublikowaniu; 0; pl


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