Mining informative patterns from very large, dynamically changing databases poses numerous interesting challenges. Data summarizations (e.g., data bubbles) have been proposed to c...
Abstract-- We investigate the problem of clustering on distributed data streams. In particular, we consider the k-median clustering on stream data arriving at distributed sites whi...
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...
Abstract. A framework for Multi Agent Data Mining (MADM) is described. The framework comprises a collection of agents cooperating to address given data mining tasks. The fundamenta...
Santhana Chaimontree, Katie Atkinson, Frans Coenen
Background The use of clustering methods for the discovery of cancer subtypes has drawn a great deal of attention in the scientific community. While bioinformaticians have propose...