An Improved Clustering Algorithm for Text Mining: Multi-Cluster Spherical K-Means

dc.authorid0000-0002-2735-7996en_US
dc.contributor.authorTunali, Volkan
dc.contributor.authorBilgin, Turgay
dc.contributor.authorCamurcu, Ali
dc.date.accessioned2024-07-12T21:49:46Z
dc.date.available2024-07-12T21:49:46Z
dc.date.issued2016en_US
dc.departmentMaltepe Üniversitesien_US
dc.description.abstractThanks to advances in information and communication technologies, there is a prominent increase in the amount of information produced specifically in the form of text documents. In order to, effectively deal with this "information explosion" problem and utilize the huge amount of text databases, efficient and scalable tools and techniques are indispensable. In this study, text clustering which is one of the most important techniques of text mining that aims at extracting useful information by processing data in textual form is addressed. An improved variant of spherical K-Means (SKM) algorithm named multi-cluster SKM is developed for clustering high dimensional document collections with high performance and efficiency. Experiments were performed on several document data sets and it is shown that the new algorithm provides significant increase in clustering quality without causing considerable difference in CPU time usage when compared to SKM algorithm.en_US
dc.identifier.endpage19en_US
dc.identifier.issn1683-3198
dc.identifier.issue1en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage12en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12415/8075
dc.identifier.volume13en_US
dc.identifier.wosWOS:000367763900002en_US
dc.identifier.wosqualityQ4en_US
dc.indekslendigikaynakWeb of Science
dc.language.isoenen_US
dc.publisherZARKA PRIVATE UNIVen_US
dc.relation.ispartofINTERNATIONAL ARAB JOURNAL OF INFORMATION TECHNOLOGYen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmzKY01271
dc.subjectData miningen_US
dc.subjecttext miningen_US
dc.subjectdocument clusteringen_US
dc.subjectSKMen_US
dc.titleAn Improved Clustering Algorithm for Text Mining: Multi-Cluster Spherical K-Meansen_US
dc.typeArticle
dspace.entity.typePublication

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