CLICKS: Mining Subspace Clusters in Categorical Data via K-Partite Maximal Cliques Mohammed Zaki and Markus Peters   View Paper (PDF)   Return to Research Session 10: Clustering Abstract We present a novel algorithm called CLICKS, that finds clusters in categorical datasets based on a search for k-partite maximal cliques. Unlike previous methods, CLICKS mines subspace clusters. It uses a selective vertical method to guarantee complete search. CLICKS outperforms previous approaches by over an order of magnitude and scales better than any of the existing method for high-dimensional datasets. We demonstrate this improvement in an excerpt from our comprehensive performance studies. ©2006 Association for Computing Machinery