Comparison of Graph Based Document Summarization Method

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dc.contributor.authorKaynar, Oguz
dc.contributor.authorGormez, Yasin
dc.contributor.authorIsik, Yunus Emre
dc.contributor.authorDemirkoparan, Ferhan
dc.date.accessioned2024-10-26T17:59:52Z
dc.date.available2024-10-26T17:59:52Z
dc.date.issued2017
dc.departmentSivas Cumhuriyet Üniversitesi
dc.description2017 International Conference on Computer Science and Engineering (UBMK) -- OCT 05-08, 2017 -- Antalya, TURKEY
dc.description.abstractToday, with the development of the internet, documents containing information such as articles, news, web pages are produced and stored in digital environment. However, the increase in the number of media where people are able to add new contents such as social media, Twitter, and blog has increased the amount of information on the internet to enormous size. However, it is very difficult and time-consuming to determine whether or not information under research is reached. Automated document summarization systems can reduce the size of the text while keeping the important part of the text and present quickly whether the text contains the desired information. In this study, graph based document summarization methods are discussed. Besides the LexRank method, TextRank algorithm is used with 4 different similarity methods. Unlike other studies, Longest Common Subsequence (LCS), a similarity measure method, is used as a measure of similarity between nodes in the TextRank algorithm. Among the similarity measurement methods used, the longest subset achieved the best success by taking 0,510 Rogue1 and 0,266 Rouge-2 scores in English dataset. Similarly, the same method yields 0,742 Rouge-1 and 0,676 Rouge-2 scores in Turkish data set, which are better than other methods.
dc.description.sponsorshipIEEE Adv Technol Human,Istanbul Teknik Univ,Gazi Univ,Atilim Univ,TBV,Akdeniz Univ,Tmmob Bilgisayar Muhendisleri Odasi
dc.identifier.endpage603
dc.identifier.isbn978-1-5386-0930-9
dc.identifier.startpage598
dc.identifier.urihttps://hdl.handle.net/20.500.12418/27380
dc.identifier.wosWOS:000426856900111
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.language.isotr
dc.publisherIEEE
dc.relation.ispartof2017 International Conference on Computer Science and Engineering (Ubmk)
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectdocument Summarization
dc.subjectlexRank
dc.subjecttextRank
dc.subjectlongest Common Subsequence
dc.titleComparison of Graph Based Document Summarization Method
dc.typeConference Object

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