A fuzzy clustering approach for finding similar documents using a novel similarity measure

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dc.contributor.authorSaracoglu, Ridvan
dc.contributor.authorTutuncu, Kemal
dc.contributor.authorAllahverdi, Novruz
dc.date.accessioned2020-03-26T17:16:55Z
dc.date.available2020-03-26T17:16:55Z
dc.date.issued2007
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractSearching for similar documents has a crucial role in document management. This paper aims for developing a fast and high quality method of searching similar documents based on fuzzy clustering in large document collections. In order to perform these requirements, a two layers structure is proposed. Formerly, finding the similarity in documents is based on the strategy that uses word-by-word comparison. The proposed method in this study uses two layers structure and lets the documents pass through it to find the similarities. In this system, predefined fuzzy clusters are used to extract feature vectors of related documents for finding similar documents of them. Similarity measure is estimated based on these vectors. To do this, a distance based similarity measure is proposed. It has been seen in empirical results that the proposed system uses new similarity measure and has better performance compared with conventional similarity measurement systems. (c) 2006 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.eswa.2006.06.002en_US
dc.identifier.endpage605en_US
dc.identifier.issn0957-4174en_US
dc.identifier.issn1873-6793en_US
dc.identifier.issue3en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage600en_US
dc.identifier.urihttps://dx.doi.org/10.1016/j.eswa.2006.06.002
dc.identifier.urihttps://hdl.handle.net/20.500.12395/21168
dc.identifier.volume33en_US
dc.identifier.wosWOS:000245754400007en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPERGAMON-ELSEVIER SCIENCE LTDen_US
dc.relation.ispartofEXPERT SYSTEMS WITH APPLICATIONSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjecttext miningen_US
dc.subjectdocument similarityen_US
dc.subjectfuzzy clusteringen_US
dc.subjectfuzzy similarity measureen_US
dc.subjectdistance based similarityen_US
dc.titleA fuzzy clustering approach for finding similar documents using a novel similarity measureen_US
dc.typeArticleen_US

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