Publication | Open Access
The Star Clustering Algorithm for Static and Dynamic Information Organization
101
Citations
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References
2004
Year
Cluster ComputingEngineeringCommunity MiningNetwork AnalysisCombinatorial Data AnalysisUnsupervised Machine LearningText MiningCluster TechnologyInformation RetrievalData ScienceData MiningStructural Graph TheorySystems EngineeringSelf-organizing MapDocument ClusteringClustering (Nuclear Physics)Knowledge DiscoveryComputer ScienceStar Clustering AlgorithmCluster DevelopmentNetwork ScienceGraph TheoryDynamic Information SystemsBusinessClustering (Data Mining)Static Information Systems
We present and analyze the off-line star algorithm for clustering static information systems and the on-line star algorithm for clustering dynamic information systems. These algorithms organize a document collection into a number of clusters that is naturally induced by the collection via a computationally efficient cover by dense subgraphs. We further show a lower bound on the quality of the clusters produced by these algorithms as well as demonstrate that these algorithms are efficient (running times roughly linear in the size of the problem). Finally, we provide data from a number of experiments. Article Type Communicated by Submitted Revised regular paper S. Khuller December 2003 August 2004 Research supported in part by ONR contract N00014-95-1-1204, DARPA contract F30602-98-2-0107, and NSF grant CCF-0418390. J. Aslam et al., The Star Clustering Algorithm, JGAA, 8(1) 95–129 (2004) 96
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