The deluge of available data for analysis demands the need to scale the performance of data mining implementations. With the current architectural trends, one of the major challen...
In many clustering applications for bioinformatics, only part of the data clusters into one or more groups while the rest needs to be pruned. For such situations, we present Hiera...
While scalable data mining methods are expected to cope with massive Web data, coping with evolving trends in noisy data in a continuous fashion, and without any unnecessary stopp...
We propose a generic framework that uses utility in decision making to drive the data mining process. We use concepts from meta-learning and build on earlier work by Elovici and B...
Abstract. The application of process mining techniques to real-life corporate environments has been of an ad-hoc nature so far, focused on proving the concept. One major reason for...