Automatic Term Extraction on Turkish Scientific Texts

dc.contributor.authorAygun, Irfan
dc.contributor.authorKaya, Mehmet
dc.date.accessioned2026-08-12T16:08:35Z
dc.date.issued2020
dc.departmentFırat Üniversitesi
dc.description2020 International Conference on Decision Aid Sciences and Application, DASA 2020 -- 7 November 2020 through 9 November 2020 -- Virtual, Sakheer -- 166557
dc.description.abstractIn order for a text or collection to be understood, it is very important to understand the terms contained in it. In this study, it is aimed to detect terms in a domain-specific (Cyber Security) corpus. A two-layer method is suggested for the determination of the terms used in single words or phrases. Term candidate words are determined by statistical methods in the first layer. In the second layer, the possibility of using these words in phrases with semantic approaches is checked. In the study, Word2Vec approach was used to determine semantic affinity and 3 different datasets were used. The results show that the terms used in singular or binary patterns were successfully determined using the proposed method. © 2020 IEEE.
dc.identifier.doi10.1109/DASA51403.2020.9317125
dc.identifier.endpage1040
dc.identifier.isbn978-172819677-0
dc.identifier.scopus2-s2.0-85100536426
dc.identifier.scopusqualityN/A
dc.identifier.startpage1037
dc.identifier.urihttps://doi.org/10.1109/DASA51403.2020.9317125
dc.identifier.urihttps://hdl.handle.net/11508/41310
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof2020 International Conference on Decision Aid Sciences and Application, DASA 2020
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_Scopus_20260511
dc.subjectinformation extraction; term extraction; terminology; text mining; word2vec
dc.titleAutomatic Term Extraction on Turkish Scientific Texts
dc.typeConference Object

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