CLICKS: Mining Subspace Clusters in Categorical Data via K-partite Maximal Cliques

We present a novel algorithm called CLICKS, that finds clusters in categorical datasets based on a search for kpartite 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.

• Type: Conference
• Year: 2005
• Where: ICDE
• Authors: Mohammed Javeed Zaki, Markus Peters
• Keywords: Algorithm Called Clicks, Clicks Mines Subspace, Database, ICDE 2005, Kpartite Maximal Cliques