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

2013
book section
conference proceedings
3
dc.abstract.enThe 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.affiliationWydział Zarządzania i Komunikacji Społecznej : Katedra Systemów Informatycznychpl
dc.conference8th International Conference on Computer Recognition Systems CORES 2013pl
dc.conference.cityMiłków
dc.conference.countryPolska
dc.conference.datefinish2013-05-29
dc.conference.datestart2013-05-27
dc.conference.indexscopustrue
dc.conference.indexwostrue
dc.contributor.authorJurek, Janusz - 128557 pl
dc.contributor.authorPeszek, Tomaszpl
dc.contributor.editorBurduk, Robertpl
dc.contributor.editorJackowski, Konradpl
dc.contributor.editorKurzyński, Marekpl
dc.contributor.editorWoźniak, Michałpl
dc.contributor.editorŻołnierek, Andrzejpl
dc.date.accessioned2014-09-23T10:56:10Z
dc.date.available2014-09-23T10:56:10Z
dc.date.issued2013pl
dc.date.openaccess0
dc.description.accesstimepo opublikowaniu
dc.description.conftypeinternationalpl
dc.description.physical101-110pl
dc.description.publication1pl
dc.description.seriesAdvances in Intelligent Systems and Computing
dc.description.seriesnumbereISSN 2194-5365
dc.description.versionostateczna wersja wydawcy
dc.description.volume1pl
dc.identifier.doi10.1007/978-3-319-00969-8_10pl
dc.identifier.eisbn978-3-319-00969-8pl
dc.identifier.isbn978-3-319-00968-1pl
dc.identifier.seriesissn2194-5357
dc.identifier.urihttp://ruj.uj.edu.pl/xmlui/handle/item/1140
dc.languageengpl
dc.language.containerengpl
dc.pubinfoCham ; New York : Springerpl
dc.rights.licenceOTHER
dc.share.typeinne
dc.subtypeConferenceProceedingspl
dc.titleModel of syntactic recognition of distorted string patterns with the help of GDPLL(k)-based automatapl
dc.title.containerProceedings of the 8th International Conference on Computer Recognition Systems CORES 2013pl
dc.typeBookSectionpl
dspace.entity.typePublication
dc.abstract.enpl
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.
dc.affiliationpl
Wydział Zarządzania i Komunikacji Społecznej : Katedra Systemów Informatycznych
dc.conferencepl
8th International Conference on Computer Recognition Systems CORES 2013
dc.conference.city
Miłków
dc.conference.country
Polska
dc.conference.datefinish
2013-05-29
dc.conference.datestart
2013-05-27
dc.conference.indexscopus
true
dc.conference.indexwos
true
dc.contributor.authorpl
Jurek, Janusz - 128557
dc.contributor.authorpl
Peszek, Tomasz
dc.contributor.editorpl
Burduk, Robert
dc.contributor.editorpl
Jackowski, Konrad
dc.contributor.editorpl
Kurzyński, Marek
dc.contributor.editorpl
Woźniak, Michał
dc.contributor.editorpl
Żołnierek, Andrzej
dc.date.accessioned
2014-09-23T10:56:10Z
dc.date.available
2014-09-23T10:56:10Z
dc.date.issuedpl
2013
dc.date.openaccess
0
dc.description.accesstime
po opublikowaniu
dc.description.conftypepl
international
dc.description.physicalpl
101-110
dc.description.publicationpl
1
dc.description.series
Advances in Intelligent Systems and Computing
dc.description.seriesnumber
eISSN 2194-5365
dc.description.version
ostateczna wersja wydawcy
dc.description.volumepl
1
dc.identifier.doipl
10.1007/978-3-319-00969-8_10
dc.identifier.eisbnpl
978-3-319-00969-8
dc.identifier.isbnpl
978-3-319-00968-1
dc.identifier.seriesissn
2194-5357
dc.identifier.uri
http://ruj.uj.edu.pl/xmlui/handle/item/1140
dc.languagepl
eng
dc.language.containerpl
eng
dc.pubinfopl
Cham ; New York : Springer
dc.rights.licence
OTHER
dc.share.type
inne
dc.subtypepl
ConferenceProceedings
dc.titlepl
Model of syntactic recognition of distorted string patterns with the help of GDPLL(k)-based automata
dc.title.containerpl
Proceedings of the 8th International Conference on Computer Recognition Systems CORES 2013
dc.typepl
BookSection
dspace.entity.type
Publication
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