Huge amounts of data are available in large-scale networks of autonomous data sources dispersed over a wide area. Data mining is an essential technology for obtaining hidden and v...
Mei Li, Guanling Lee, Wang-Chien Lee, Anand Sivasu...
Practical clustering algorithms require multiple data scans to achieve convergence. For large databases, these scans become prohibitively expensive. We present a scalable clusteri...
The growing dominance of wire delays at future technology points renders a microprocessor communication-bound. Clustered microarchitectures allow most dependence chains to execute...
In this paper, we devise an efficient algorithm for clustering market-basket data. Different from those of the traditional data, the features of market-basket data are known to b...
Background: Clustering of gene expression patterns is a well-studied technique for elucidating trends across large numbers of transcripts and for identifying likely co-regulated g...