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» Distributed Data Mining Models as Services on the Grid
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ICDM
2003
IEEE
210views Data Mining» more  ICDM 2003»
15 years 11 months ago
CBC: Clustering Based Text Classification Requiring Minimal Labeled Data
Semi-supervised learning methods construct classifiers using both labeled and unlabeled training data samples. While unlabeled data samples can help to improve the accuracy of trai...
Hua-Jun Zeng, Xuanhui Wang, Zheng Chen, Hongjun Lu...
ICDM
2007
IEEE
138views Data Mining» more  ICDM 2007»
15 years 10 months ago
Preserving Privacy through Data Generation
Many databases will not or can not be disclosed without strong guarantees that no sensitive information can be extracted. To address this concern several data perturbation techniq...
Jilles Vreeken, Matthijs van Leeuwen, Arno Siebes
ICDM
2009
IEEE
223views Data Mining» more  ICDM 2009»
16 years 1 months ago
Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis
Abstract -- Detection of execution anomalies is very important for the maintenance, development, and performance refinement of large scale distributed systems. Execution anomalies ...
Qiang Fu, Jian-Guang Lou, Yi Wang, Jiang Li
GIS
2006
ACM
16 years 7 months ago
ST-ACTS: a spatio-temporal activity simulator
Creating complex spatio?temporal simulation models is a hot issue in the area of spatio?temporal databases [7]. While existing Moving Object Simulators (MOSs) address different ph...
Gyözö Gidófalvi, Torben Bach Pede...
SDM
2007
SIAM
198views Data Mining» more  SDM 2007»
15 years 7 months ago
Learning from Time-Changing Data with Adaptive Windowing
We present a new approach for dealing with distribution change and concept drift when learning from data sequences that may vary with time. We use sliding windows whose size, inst...
Albert Bifet, Ricard Gavaldà