5 search results - page 1 / 1 » A martingale framework for concept change detection in time-... |
ICML
2005
IEEE
14 years 5 months ago
2005
IEEE
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...
IJCAI
2007
13 years 5 months ago
2007
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...
CIKM
2010
Springer
13 years 3 months ago
2010
Springer
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...
WWW
2009
ACM
13 years 11 months ago
2009
ACM
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...
SDM
2009
SIAM
14 years 1 months ago
2009
SIAM
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...