K-Means clustering is widely used in information retrieval and data mining. Distributed K-Means variants have already been proposed, but none of the past algorithms scales to large...
Odysseas Papapetrou, Wolf Siberski, Fabian Leitrit...
Active data clustering is a novel technique for clustering of proximity data which utilizes principles from sequential experiment design in order to interleave data generation and...
We address here two major challenges presented by dynamic data mining: 1) the stability challenge: we have implemented a rigorous incremental density-based clustering algorithm, i...
Today's world is characterized by the multiplicity of interconnections through many types of links between the people, that is why mining social networks appears to be an impo...
We present an efficient, fully automated algorithm to assemble ESTs into full-length cDNA sequences that represent the complete coding regions of a gene. Our EST clustering algori...
Arthur Grossman, Charles Hauser, Hilary J. Holz, J...