In this demo, we present Nile-PDT, a Phenomenon Detection and Tracking framework using the Nile data stream management system. A phenomenon is characterized by a group of streams ...
Mohamed H. Ali, Walid G. Aref, Raja Bose, Ahmed K....
In the last few years, we have been witnessing an evergrowing need for continuous observation and monitoring applications. This need is driven by recent technological advances that...
Themis Palpanas, Vana Kalogeraki, Dimitrios Gunopu...
— Quantiles are very useful in characterizing the data distribution of an evolving dataset in the process of data mining or network monitoring. The method of Stochastic Approxima...
Abstract. We propose a novel framework of autonomic intrusion detection that fulfills online and adaptive intrusion detection in unlabeled audit data streams. The framework owns a...
: This paper presents a system for induction of forest of functional trees from data streams able to detect concept drift. The Ultra Fast Forest of Trees (UFFT) is an incremental a...