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dc.contributor.authorKarasoy, Onur
dc.contributor.authorBallı, Serkan
dc.date.accessioned2020-11-20T14:53:57Z
dc.date.available2020-11-20T14:53:57Z
dc.date.issued2017
dc.identifier.isbn978-1-5386-0930-9
dc.identifier.urihttps://hdl.handle.net/20.500.12809/2084
dc.description2017 International Conference on Computer Science and Engineering (UBMK) - OCT 05-08, 2017 - Antalya, TURKEYen_US
dc.description0000-0002-4825-139Xen_US
dc.descriptionWOS: 000426856900055en_US
dc.description.abstractIn this study, it was aimed to develop SMS (Short Message) classification application based on deep learning. By examining messages collected from different age groups and regions, feature labels that could be effective in classification were included in the message data set. After that, the model to he used in the classification was created through Word2Vec library. With this model, new features were extracted, test messages were classified and analyzed, and the results were discussed.en_US
dc.description.sponsorshipIEEE Adv Technol Human, Istanbul Teknik Univ, Gazi Univ, Atilim Univ, TBV, Akdeniz Univ, Tmmob Bilgisayar Muhendisleri Odasien_US
dc.item-language.isoturen_US
dc.publisherIeeeen_US
dc.item-rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectWord2vecen_US
dc.subjectShort Messageen_US
dc.subjectSins Classificationen_US
dc.subjectSms Filteringen_US
dc.titleClassification Turkish SMS with Deep Learning Tool Word2Vecen_US
dc.item-typeconferenceObjecten_US
dc.contributor.departmentMÜ, Teknoloji Fakültesi, Bilişim Sistemleri Mühendisliği Bölümüen_US
dc.contributor.institutionauthorBallı, Serkan
dc.identifier.startpage294en_US
dc.identifier.endpage297en_US
dc.relation.journal2017 International Conference on Computer Science and Engineering (Ubmk)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US


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