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SDM
2009
SIAM
291views Data Mining» more  SDM 2009»
16 years 3 months ago
Detection and Characterization of Anomalies in Multivariate Time Series.
Anomaly detection in multivariate time series is an important data mining task with applications to ecosystem modeling, network traffic monitoring, medical diagnosis, and other d...
Christopher Potter, Haibin Cheng, Pang-Ning Tan, S...
PKDD
2009
Springer
175views Data Mining» more  PKDD 2009»
16 years 1 months ago
Latent Dirichlet Bayesian Co-Clustering
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...
Pu Wang, Carlotta Domeniconi, Kathryn B. Laskey
ICDM
2008
IEEE
142views Data Mining» more  ICDM 2008»
16 years 1 months ago
Clustering Events on Streams Using Complex Context Information
Monitoring applications play an increasingly important role in many domains. They detect events in monitored systems and take actions such as invoke a program or notify an adminis...
YongChul Kwon, Wing Yee Lee, Magdalena Balazinska,...
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ICDCS
2006
IEEE
16 years 21 days ago
Scalable and Robust Aggregation Techniques for Extracting Statistical Information in Sensor Networks
Wireless sensor networks have stringent constraints on system resources and data aggregation techniques are critically important. However, accurate data aggregation is difficult ...
Hongbo Jiang, Shudong Jin
ICDCSW
2005
IEEE
16 years 7 days ago
Adaptive Real-Time Anomaly Detection with Improved Index and Ability to Forget
Anomaly detection in IP networks, detection of deviations from what is considered normal, is an important complement to misuse detection based on known attack descriptions. Perfor...
Kalle Burbeck, Simin Nadjm-Tehrani