Text classification of web based news articles by using Turkish grammatical features

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dc.authorscopusid11539603200
dc.authorscopusid54783608800
dc.authorscopusid55292742900
dc.contributor.authorTüfekçi, Pınar
dc.contributor.authorUzun, Erdinç
dc.contributor.authorSevinç, Burak
dc.date.accessioned2022-05-11T14:15:46Z
dc.date.available2022-05-11T14:15:46Z
dc.date.issued2012
dc.departmentFakülteler, Çorlu Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü
dc.description2012 20th Signal Processing and Communications Applications Conference, SIU 2012 -- 18 April 2012 through 20 April 2012 -- Fethiye, Mugla -- 90786
dc.description.abstractThe dimensions of the feature vectors being used at the classification methods in the literature affect directly the time performance. In this study, how to reduce the dimension of the feature vector by using Turkish's grammar rules without compromising success rates is explained. The feature vector is weighted on the basis of the word frequency as the word stems have been selected as features. During this selection the effects of selection of the word stems with different length and type to the classification are investigated and when the word stems with noun type and the maximum length are selected as features, the success rate has been found to be at the highest level. When this selection is applied with the other methods which reduce the dimension, the dimension of the feature vector is decreased to 97.46%. Using the reduced feature vector the better succes rates generally have been obtained from Naive Bayes, SVM, C 4.5 and RF classification methods and the best performance achieved is 92.73% which has been obtained using the Naive Bayes method. © 2012 IEEE.
dc.identifier.doi10.1109/SIU.2012.6204565
dc.identifier.isbn978-1467300568
dc.identifier.scopus2-s2.0-84863443667
dc.identifier.urihttps://doi.org/10.1109/SIU.2012.6204565
dc.identifier.urihttps://hdl.handle.net/20.500.11776/6067
dc.indekslendigikaynakScopus
dc.institutionauthorTüfekçi, Pınar
dc.institutionauthorUzun, Erdinç
dc.institutionauthorSevinç, Burak
dc.language.isotr
dc.relation.ispartof2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedings
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectClassification methods
dc.subjectFeature vectors
dc.subjectGrammar rules
dc.subjectNaive bayes
dc.subjectNews articles
dc.subjectText classification
dc.subjectTime performance
dc.subjectTurkishs
dc.subjectWeb based
dc.subjectWord frequencies
dc.subjectSignal processing
dc.subjectClassifiers
dc.titleText classification of web based news articles by using Turkish grammatical features
dc.title.alternativeTürkçe di?lbi?lgi?si? özelli? kleri?ni? kullanarak web tabanli haber meti?nleri?ni?n siniflandirilmasi]
dc.typeConference Object

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