The star clustering algorithm for information organization

Abstract

We present the star clustering algorithm for static and dynamic information organization. The offline star algorithm can be used for clustering static information systems, and the online star algorithm can be used for clustering dynamic information systems. These algorithms organize a data collection into a number of clusters that are naturally induced by the collection via a computationally efficient cover by dense subgraphs. We further show a lower bound on the accuracy of the clusters produced by these algorithms as well as demonstrate that these algorithms are computationally efficient. Finally, we discuss a number of applications of the star clustering algorithm and provide results from a number of experiments with the Text Retrieval Conference data. © 2006 Springer-Verlag Berlin Heidelberg.