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dc.contributor.authorKilic, Erdal
dc.contributor.authorAtes, Nurullah
dc.contributor.authorKarakaya, Aykut
dc.contributor.authorSahin, Durmus Ozkan
dc.date.accessioned2020-06-21T13:51:04Z
dc.date.available2020-06-21T13:51:04Z
dc.date.issued2015
dc.identifier.isbn978-1-4673-7386-9
dc.identifier.issn2165-0608
dc.identifier.urihttps://hdl.handle.net/20.500.12712/14568
dc.description23nd Signal Processing and Communications Applications Conference (SIU) -- MAY 16-19, 2015 -- Inonu Univ, Malatya, TURKEYen_US
dc.descriptionSahin, Durmus Ozkan/0000-0002-0831-7825; Karakaya, Aykut/0000-0001-6970-3239en_US
dc.descriptionWOS: 000380500900097en_US
dc.description.abstractIn this study, two new document weighting methods are proposed based on term frequency-inverse document frequency (TF-IDF) generally used in text mining methods. Also, insignificance of the verb in text classification which will be a new method in pre-processing have been put forward and tested. The better results were observed through using these methods when these methods compare with other method, It was observed that the performance rate hardly change and the data size which was processed decreased by omitting verbs of texts.en_US
dc.description.sponsorshipDept Comp Engn & Elect & Elect Engn, Elect & Elect Engn, Bilkent Univen_US
dc.language.isoturen_US
dc.publisherIeeeen_US
dc.relation.ispartofseriesSignal Processing and Communications Applications Conference
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjecttext classificationen_US
dc.subjectterm weightingen_US
dc.subjectinverse document frequencyen_US
dc.titleTwo New Feature Extraction Methods for Text Classification: TESDF and SADFen_US
dc.typeconferenceObjecten_US
dc.contributor.departmentOMÜen_US
dc.identifier.startpage475en_US
dc.identifier.endpage478en_US
dc.relation.journal2015 23Rd Signal Processing and Communications Applications Conference (Siu)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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