Most existing methods of semi-supervised clustering introduce supervision from outside, e.g., manually label some data samples or introduce constrains into clustering results. Thi...
Abstract-- Simultaneously clustering columns and rows (coclustering) of large data matrix is an important problem with wide applications, such as document mining, microarray analys...
The use of multiprocessor tasks (M-tasks) has been shown to be successful for mixed task and data parallel implementations of algorithms from scientific computing. The approach o...
Many Internet-based applications have adopted XML as the standard data exchange format. These XML data are typically stored in its native form, thus creating the need to present XM...
Modern science is collecting massive amounts of data from sensors, instruments, and through computer simulation. It is widely believed that analysis of this data will hold the key ...