With the advent of high-performance COTS clusters, there is a need for a simple, scalable and faulttolerant parallel programming and execution paradigm. In this paper, we show that...
Reza Farivar, Abhishek Verma, Ellick Chan, Roy H. ...
Data clustering methods have been proven to be a successful data mining technique in the analysis of gene expression data. The Cluster affinity search technique (CAST) developed b...
Abdelghani Bellaachia, David Portnoy, Yidong Chen,...
Many applications in wireless sensor networks (WSNs) benefit significantly from organizing nodes into groups, called clusters, because data aggregation and data filtering applied i...
This paper centers on the discussion of k-medoid-style clustering algorithms for supervised summary generation. This task requires clustering techniques that identify class-unifor...
Combining multiple clusterings arises in various important data mining scenarios. However, finding a consensus clustering from multiple clusterings is a challenging task because ...