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...
Likelihood-based marginal regression modelling for repeated, or otherwise clustered, categorical responses is computationally demanding. This is because the number of measures nee...