In a data streaming setting, data points are observed one by one. The concepts to be learned from the data points may change infinitely often as the data is streaming. In this pap...
The martingale framework for detecting changes in data stream, currently only applicable to labeled data, is extended here to unlabeled data using clustering concept. The one-pass...
The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
Detection of web attacks is an important issue in current defense-in-depth security framework. In this paper, we propose a novel general framework for adaptive and online detectio...
Wei Wang 0012, Florent Masseglia, Thomas Guyet, Re...
The primary constraint in the effective mining of data streams is the large volume of data which must be processed in real time. In many cases, it is desirable to store a summary...