Deep Neural Network Architecture for Part-of-Speech Tagging for Turkish Language

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dc.authoridYildiz, Tugba/0000-0002-8552-2806
dc.authorwosidYildiz, Tugba/ABC-5958-2020
dc.contributor.authorBahcevan, Cenk Anil
dc.contributor.authorKutlu, Emirhan
dc.contributor.authorYildiz, Tugba
dc.date.accessioned2024-07-18T20:50:56Z
dc.date.available2024-07-18T20:50:56Z
dc.date.issued2018
dc.departmentİstanbul Bilgi Üniversitesien_US
dc.description3rd International Conference on Computer Science and Engineering (UBMK) -- SEP 20-23, 2018 -- Sarajevo, BOSNIA & HERCEGen_US
dc.description.abstractParts of Speech (POS) tagging is one of the most well-studied problems in the field of Natural Language Processing (NLP). In this paper, a Neural Network Language Models (NNLM) such as Recurrent Neural Network (RNN) and Long Short Term Memory (LSTM) have been trained and assessed to address the POS tagging problem for the Turkish Language. The performance is compared to the state-of-art methods. The results show that LSTM outperl4ms RNN with 88.7% Fl-score. This study is the first study that contributes to the literature utilizing word embedding and NNLM for the Turkish language.en_US
dc.description.sponsorshipBMBB,Istanbul Teknik Univ,Gazi Univ,ATILIM Univ,Int Univ Sarajevo,Kocaeli Univ,TURKiYE BiLiSiM VAKFIen_US
dc.identifier.endpage238en_US
dc.identifier.isbn978-1-5386-7893-0
dc.identifier.scopus2-s2.0-85060639088en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage235en_US
dc.identifier.urihttps://hdl.handle.net/11411/8292
dc.identifier.wosWOS:000459847400044en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.relation.ispartof2018 3rd International Conference on Computer Science and Engineering (Ubmk)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPart Of Speech Taggingen_US
dc.subjectRecurrent Neural Networken_US
dc.subjectLong-Short Term Memoryen_US
dc.subjectDeep Learningen_US
dc.subjectFasttexten_US
dc.titleDeep Neural Network Architecture for Part-of-Speech Tagging for Turkish Languageen_US
dc.typeConference Objecten_US

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