Existing data-stream clustering algorithms such as CluStream are based on k-means. These clustering algorithms are incompetent to find clusters of arbitrary shapes and cannot hand...
Scientists increasingly use ensemble data sets to explore relationships present in dynamic systems. Ensemble data sets combine spatio-temporal simulation results generated using mu...
Kristin Potter, Andrew Wilson, Peer-Timo Bremer, D...
Educators developing data mining courses face a difficult task of designing curricula that are adaptable, have solid foundations, and are tailored to students from different acade...
Abstract. Integrating data mining into business processes becomes crucial for business today. Modern business process management frameworks provide great support for flexible desig...
Data mining focuses on the development of methods and algorithms for such tasks as classification, clustering, rule induction, and discovery of associations. In the database fiel...