77 search results - page 4 / 16 » Systematic data selection to mine concept-drifting data stre... |
KDD
2009
ACM
14 years 8 months ago
2009
ACM
Advanced analysis of data streams is quickly becoming a key area of data mining research as the number of applications demanding such processing increases. Online mining when such...
KDD
2003
ACM
14 years 8 months ago
2003
ACM
Recently, mining data streams with concept drifts for actionable insights has become an important and challenging task for a wide range of applications including credit card fraud...
COMAD
2009
13 years 8 months ago
2009
Mining evolving data streams for concept drifts has gained importance in applications like customer behavior analysis, network intrusion detection, credit card fraud detection. Se...
DIS
2004
Springer
14 years 1 months ago
2004
Springer
The two main challenges typically associated with mining data streams are concept drift and data contamination. To address these challenges, we seek learning techniques and models ...
EUROGP
2007
Springer
14 years 1 months ago
2007
Springer
A Genetic Programming based boosting ensemble method for the classification of distributed streaming data is proposed. The approach handles flows of data coming from multiple loc...