Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
A data stream is a massive unbounded sequence of data elements continuously generated at a rapid rate. Consequently, the knowledge embedded in a data stream is more likely to be c...
Predictive models developed by applying Data Mining techniques are used to improve forecasting accuracy in the airline business. In order to maximize the revenue on a flight, the ...
The continued scaling of device dimensions and the operating voltage reduces the critical charge and thus natural noise tolerance level of transistors. As a result, circuits can p...
Scalability of applications on distributed sharedmemory (DSM) multiprocessors is limited by communication overheads. At some point, using more processors to increase parallelism y...
Khaled Z. Ibrahim, Gregory T. Byrd, Eric Rotenberg