Improving the BERT Model with Proposed Named Entity Recognition Method for Question Answering

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dc.authorscopusid57202999818
dc.authorscopusid6506739590
dc.contributor.authorGuven Z.A.
dc.contributor.authorUnalir M.O.
dc.date.accessioned2023-01-12T20:23:22Z
dc.date.available2023-01-12T20:23:22Z
dc.date.issued2021
dc.departmentN/A/Departmenten_US
dc.description6th International Conference on Computer Science and Engineering, UBMK 2021 -- 15 September 2021 through 17 September 2021 -- -- 176826en_US
dc.description.abstractRecently, the analysis of textual data has gained importance due to the increase in comments made on web platforms and the need for ready-made answering systems. Therefore, there are many studies in the fields of natural language processing such as text summarization and question answering. In this paper, the accuracy of the B E R T language model is analyzed for the question answering domain, which allows to automatically answer a question asked. Using SQuAD, one of the reading comprehension datasets, the answers to the questions that the B E R T model cannot answer are researched with the proposed Named Entity Recognition method in natural language processing. The accuracy of B E R T models used with the proposed Named Entity Recognition method increases between 1.7% and 2.7%. As a result of the analysis, it is shown that the B E R T model doesn't use Named Entity Recognition technique sufficiently. © 2021 IEEEen_US
dc.identifier.doi10.1109/UBMK52708.2021.9558992
dc.identifier.endpage208en_US
dc.identifier.isbn9781665429085
dc.identifier.scopus2-s2.0-85125832170en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage204en_US
dc.identifier.urihttps://doi.org/10.1109/UBMK52708.2021.9558992
dc.identifier.urihttps://hdl.handle.net/11454/79695
dc.indekslendigikaynakScopusen_US
dc.language.isotren_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.subjectBERTen_US
dc.subjectData Analysisen_US
dc.subjectNamed Entity Recognitionen_US
dc.subjectNatural Language Processingen_US
dc.subjectQuestion Answeringen_US
dc.subjectAnalysis of textual datumen_US
dc.subjectBERTen_US
dc.subjectData analyseen_US
dc.subjectLanguage modelen_US
dc.subjectNamed entity recognitionen_US
dc.subjectQuestion Answeringen_US
dc.subjectReading comprehensionen_US
dc.subjectRecognition methodsen_US
dc.subjectT-modelen_US
dc.subjectText Summarisationen_US
dc.subjectNatural language processing systemsen_US
dc.titleImproving the BERT Model with Proposed Named Entity Recognition Method for Question Answeringen_US
dc.title.alternativeÖnerilen Varlik Ismi Tanima Yöntemi ile Soru Cevaplamada BERT Modelinin lyileçtirilmesien_US
dc.typeConference Objecten_US

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