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» Detecting Change in Data Streams
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CIKM
2010
Springer
13 years 6 months ago
Partial drift detection using a rule induction framework
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...
Damon Sotoudeh, Aijun An
ICDM
2007
IEEE
159views Data Mining» more  ICDM 2007»
14 years 2 months ago
Incremental Subspace Clustering over Multiple Data Streams
Data streams are often locally correlated, with a subset of streams exhibiting coherent patterns over a subset of time points. Subspace clustering can discover clusters of objects...
Qi Zhang, Jinze Liu, Wei Wang 0010
DSN
2008
IEEE
14 years 2 months ago
Anomaly? application change? or workload change? towards automated detection of application performance anomaly and change
: Automated tools for understanding application behavior and its changes during the application life-cycle are essential for many performance analysis and debugging tasks. Applicat...
Ludmila Cherkasova, Kivanc M. Ozonat, Ningfang Mi,...
ASC
2008
13 years 7 months ago
Info-fuzzy algorithms for mining dynamic data streams
Most data mining algorithms assume static behavior of the incoming data. In the real world, the situation is different and most continuously collected data streams are generated by...
Lior Cohen, Gil Avrahami, Mark Last, Abraham Kande...
EMNLP
2010
13 years 5 months ago
We're Not in Kansas Anymore: Detecting Domain Changes in Streams
Domain adaptation, the problem of adapting a natural language processing system trained in one domain to perform well in a different domain, has received significant attention. Th...
Mark Dredze, Tim Oates, Christine D. Piatko