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A new approach for named entity recognition

dc.contributor.authorErtopçu, Buraken_US
dc.contributor.authorKanburoğlu, Ali Buğraen_US
dc.contributor.authorTopsakal, Ozanen_US
dc.contributor.authorAçıkgöz, Onuren_US
dc.contributor.authorGürkan, Ali Tuncaen_US
dc.contributor.authorÖzenç, Berkeen_US
dc.contributor.authorAvar, Begümen_US
dc.contributor.authorErcan, Gökhanen_US
dc.contributor.authorYıldız, Olcay Taneren_US
dc.contributor.authorÇam, İlkeren_US
dc.date.accessioned2019-03-27T04:31:01Z
dc.date.available2019-03-27T04:31:01Z
dc.date.issued2017
dc.identifier.citationErtopçu, B., Kanburoğlu, A. B., Topsakal, O., Açıkgöz, O., Gürkan, A. T., Özenç, B., Avar, B., Ercan, G., Çam, İ. & Yıldız, O. T. (2017). A new approach for named entity recognition. Paper presented at the 2nd International Conference on Computer Science and Engineering, UBMK 2017, 474-479. doi:10.1109/UBMK.2017.8093439en_US
dc.identifier.isbn9781538609309
dc.identifier.urihttps://hdl.handle.net/11729/1513
dc.identifier.urihttp://dx.doi.org/10.1109/UBMK.2017.8093439
dc.description.abstractMany sentences create certain impressions on people. These impressions help the reader to have an insight about the sentence via some entities. In NLP, this process corresponds to Named Entity Recognition (NER). NLP algorithms can trace a lot of entities in the sentence like person, location, date, time or money. One of the major problems in these operations are confusions about whether the word denotes the name of a person, a location or an organisation, or whether an integer stands for a date, time or money. In this study, we design a new model for NER algorithms. We train this model in our predefined dataset and compare the results with other models. In the end we get considerable outcomes in a dataset containing 1400 sentences.en_US
dc.description.sponsorshipThis work was supported by Isik University BAP projects 14B206 and 15B201. All authors contributed equally to this work. O. A., I. C., B. E., A. T. G., A. B. K., B. O., O. T. designed and implemented discrete model experiments. They also labeled the data and wrote the manuscript. G. E. designed and implemented continuous model experiments. B. A. wrote the manuscript. O. T. Y. supervised the project, gave conceptual advice and wrote the manuscripten_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.relation.isversionof10.1109/UBMK.2017.8093439
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectNatural language processingen_US
dc.subjectInformation extrac-tionen_US
dc.subjectNamed entity recognitionen_US
dc.subjectAlgorithm design and analysisen_US
dc.subjectCompaniesen_US
dc.subjectTaggingen_US
dc.subjectFeature extractionen_US
dc.subjectText analysisen_US
dc.subjectNER algorithmsen_US
dc.subjectNLP algorithmsen_US
dc.titleA new approach for named entity recognitionen_US
dc.typeconferenceObjecten_US
dc.description.versionPublisher's Versionen_US
dc.relation.journal2nd International Conference on Computer Science and Engineering, UBMK 2017en_US
dc.contributor.departmentIşık Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümüen_US
dc.contributor.departmentIşık University, Faculty of Engineering, Department of Computer Engineeringen_US
dc.contributor.authorID0000-0003-2008-243X
dc.contributor.authorID0000-0001-5838-4615
dc.contributor.authorID0000-0002-2782-8217
dc.identifier.startpage474
dc.identifier.endpage479
dc.peerreviewedYesen_US
dc.publicationstatusPublisheden_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.contributor.institutionauthorErtopçu, Buraken_US
dc.contributor.institutionauthorKanburoğlu, Ali Buğraen_US
dc.contributor.institutionauthorTopsakal, Ozanen_US
dc.contributor.institutionauthorAçıkgöz, Onuren_US
dc.contributor.institutionauthorGürkan, Ali Tuncaen_US
dc.contributor.institutionauthorÖzenç, Berkeen_US
dc.contributor.institutionauthorErcan, Gökhanen_US
dc.contributor.institutionauthorYıldız, Olcay Taneren_US
dc.contributor.institutionauthorÇam, İlkeren_US
dc.relation.indexWOSen_US
dc.relation.indexScopusen_US
dc.relation.indexConference Proceedings Citation Index – Science (CPCI-S)en_US
dc.description.wosidWOS:000426856900088


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