Abstract— Recently we proposed algorithms for concurrent execution on multiple clusters [9]. In this case, data partitioning is done at two levels; first, the data is distribute...
Chen Yu, Dan C. Marinescu, Howard Jay Siegel, John...
Clustering is the problem of identifying the distribution of patterns and intrinsic correlations in large data sets by partitioning the data points into similarity classes. This p...
Advances in wireless networks and positioning technologies (e.g., GPS) have enabled new data management applications that monitor moving objects. In such new applications, realtime...
Subspace clustering (also called projected clustering) addresses the problem that different sets of attributes may be relevant for different clusters in high dimensional feature sp...
Users of Web search engines are often forced to sift through the long ordered list of document “snippets” returned by the engines. The IR community has explored document cluste...