Uncertain data streams, where data is incomplete, imprecise, and even misleading, have been observed in many environments. Feeding such data streams to existing stream systems pro...
Thanh T. L. Tran, Liping Peng, Boduo Li, Yanlei Di...
Data stream clustering has emerged as a challenging and interesting problem over the past few years. Due to the evolving nature, and one-pass restriction imposed by the data strea...
Abstract. Ensemble methods are popular learning methods that usually increase the predictive accuracy of a classifier though at the cost of interpretability and insight in the deci...
Many applicationsstore data items for a pre-determined, finite length of time. Examples include slidingwindows over on-line data streams, where old data are dropped as the window...
The increasing availability of streaming data is a consequence of the continuing advancement of data acquisition technology. Such data provides new challenges to the various data a...
Dimitris K. Tasoulis, Gordon J. Ross, Niall M. Ada...