In recent years, emerging applications introduced new constraints for data mining methods. These constraints are typical of a new kind of data: the data streams. In data stream pro...
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
Abstract— We describe a grid-based approach for enterprisescale data mining that leverages database technology for I/O parallelism, and on-demand compute servers for compute para...
Business information received from advanced data analysis and data mining is a critical success factor for companies wishing to maximize competitive advantage. The use of tradition...
The knowledge discovery process is interactive in nature and therefore minimizing query response time is imperative. The compute and memory intensive nature of data mining algorit...
Amol Ghoting, Gregory Buehrer, Matthew Goyder, Shi...