Please use this identifier to cite or link to this item: https://scholarbank.nus.edu.sg/handle/10635/41071
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dc.titleJourney to the centre of the star: Various ways of finding star centers in star clustering
dc.contributor.authorWijaya, D.T.
dc.contributor.authorBressan, S.
dc.date.accessioned2013-07-04T08:18:57Z
dc.date.available2013-07-04T08:18:57Z
dc.date.issued2007
dc.identifier.citationWijaya, D.T.,Bressan, S. (2007). Journey to the centre of the star: Various ways of finding star centers in star clustering. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4653 LNCS : 660-670. ScholarBank@NUS Repository.
dc.identifier.isbn9783540744672
dc.identifier.issn03029743
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/41071
dc.description.abstractThe Star algorithm is an effective and efficient algorithm for graph clustering. We propose a series of novel, yet simple, metrics for the selection of Star centers in the Star algorithm and its variants. We empirically study the performance of off-line, standard and extended, and on-line versions of the Star algorithm adapted to the various metrics and show that one of the proposed metrics outperforms all others in both effectiveness and efficiency of clustering. We empirically study the sensitivity of the metrics to the threshold value of the algorithm and show improvement with respect to this aspect too. © Springer-Verlag Berlin Heidelberg 2007.
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentCOMPUTER SCIENCE
dc.description.sourcetitleLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.description.volume4653 LNCS
dc.description.page660-670
dc.identifier.isiutNOT_IN_WOS
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