Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
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...
The Web has been rapidly "deepened" by myriad searchable databases online, where data are hidden behind query interfaces. As an essential task toward integrating these m...
The popularity of email has triggered researchers to look for ways to help users better organize the enormous amount of information stored in their email folders. One challenge th...
Discovery of sequential patterns is an essential data mining task with broad applications. Among several variations of sequential patterns, closed sequential pattern is the most u...
In an interactive classification application, a user may find it more valuable to develop a diagnostic decision support method which can reveal significant classification behavior...
While the vast majority of clustering algorithms are partitional, many real world datasets have inherently overlapping clusters. Several approaches to finding overlapping clusters...
Visitors enter a website through a variety of means, including web searches, links from other sites, and personal bookmarks. In some cases the first page loaded satisfies the visi...
Justin Brickell, Inderjit S. Dhillon, Dharmendra S...