Static and dynamic information organization with star clusters
Proceedings of the seventh international conference on Information and knowledge management
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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 partition a document collection into a number of clusters that is naturally induced by the collection. We show a lower bound on the accuracy of the clusters produced by these algorithms. We use the random graph model to show that both star algorithms produce correct clusters in time Theta(V + E). Finally, we provide data from extensive experiments.