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IJCNN
2006
IEEE
14 years 1 months ago
A computational intelligence-based criterion to detect non-stationarity trends
—The stationarity hypothesis is largely and implicitly assumed when designing classifiers (especially those for industrial applications) but it does not generally hold in practic...
Cesare Alippi, Manuel Roveri
PAKDD
2009
ACM
149views Data Mining» more  PAKDD 2009»
14 years 9 hour ago
A New Local Distance-Based Outlier Detection Approach for Scattered Real-World Data
Detecting outliers which are grossly different from or inconsistent with the remaining dataset is a major challenge in real-world KDD applications. Existing outlier detection met...
Ke Zhang, Marcus Hutter, Huidong Jin
ICDCS
2010
IEEE
13 years 11 months ago
Sentomist: Unveiling Transient Sensor Network Bugs via Symptom Mining
—Wireless Sensor Network (WSN) applications are typically event-driven. While the source codes of these applications may look simple, they are executed with a complicated concurr...
Yangfan Zhou, Xinyu Chen, Michael R. Lyu, Jiangchu...
IMC
2010
ACM
13 years 5 months ago
Temporally oblivious anomaly detection on large networks using functional peers
Previous methods of network anomaly detection have focused on defining a temporal model of what is "normal," and flagging the "abnormal" activity that does not...
Kevin M. Carter, Richard Lippmann, Stephen W. Boye...
ICDM
2009
IEEE
148views Data Mining» more  ICDM 2009»
14 years 2 months ago
Online System Problem Detection by Mining Patterns of Console Logs
Abstract—We describe a novel application of using data mining and statistical learning methods to automatically monitor and detect abnormal execution traces from console logs in ...
Wei Xu, Ling Huang, Armando Fox, David Patterson, ...