A Practical Clustering Algorithm for Static and Dynamic Information Organization

Abstract

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