Topic Modeling Using LDA and BERT Techniques: Teknofest Example

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dc.authorscopusid56557054300
dc.authorscopusid57479135600
dc.authorscopusid57189887324
dc.contributor.authorAtagün, Ercan
dc.contributor.authorHartoka, B.
dc.contributor.authorAlbayrak, Ahmet
dc.date.accessioned2023-07-26T11:54:52Z
dc.date.available2023-07-26T11:54:52Z
dc.date.issued2021
dc.departmentDÜ, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.description6th International Conference on Computer Science and Engineering, UBMK 2021 -- 15 September 2021 through 17 September 2021 -- 176826en_US
dc.description.abstractThis paper is a natural language processing study and includes models used in natural language processing. In this paper, topic modeling, which is one of the sub-fields of natural language processing, has been studied. In order to make topic modeling, the data set was obtained by using the data scraping method, which has been very popular in recent years, over social media. The dataset is related to Teknofest competitions. The dataset was created by utilizing the Selenium library, one of the popular libraries used for the data scraping method. In order to be able to analyze on the prepared data set and to ensure the consistency of the clustering process, the text to be used before the analysis was preprocessed. After text preprocessing, clustering was performed on the data set with natural language processing techniques such as BERT and LDA . © 2021 IEEEen_US
dc.identifier.doi10.1109/UBMK52708.2021.9558988
dc.identifier.endpage664en_US
dc.identifier.isbn9.78167E+12
dc.identifier.scopus2-s2.0-85125846132en_US
dc.identifier.startpage660en_US
dc.identifier.urihttps://doi.org/10.1109/UBMK52708.2021.9558988
dc.identifier.urihttps://hdl.handle.net/20.500.12684/12944
dc.indekslendigikaynakScopusen_US
dc.institutionauthorAtagün, Ercan
dc.institutionauthorHartoka, B.
dc.institutionauthorAlbayrak, Ahmet
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - 6th International Conference on Computer Science and Engineering, UBMK 2021en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz$2023V1Guncelleme$en_US
dc.subjectBerten_US
dc.subjectData Scrapingen_US
dc.subjectLDAen_US
dc.subjectTeknofesten_US
dc.subjectTopic Modelingen_US
dc.subjectClustering algorithmsen_US
dc.subjectModeling languagesen_US
dc.subjectBerten_US
dc.subjectClustering processen_US
dc.subjectData scrapingen_US
dc.subjectData seten_US
dc.subjectLDAen_US
dc.subjectSocial mediaen_US
dc.subjectSub fieldsen_US
dc.subjectTeknofesten_US
dc.subjectText preprocessingen_US
dc.subjectTopic Modelingen_US
dc.subjectNatural language processing systemsen_US
dc.titleTopic Modeling Using LDA and BERT Techniques: Teknofest Exampleen_US
dc.typeConference Objecten_US

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