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» Anomaly Detection Using Process Mining
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CIKM
2010
Springer
13 years 8 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
2003
IEEE
184views Data Mining» more  ICDM 2003»
14 years 2 months ago
Detecting Patterns of Change Using Enhanced Parallel Coordinates Visualization
Analyzing data to find trends, correlations, and stable patterns is an important problem for many industrial applications. In this paper, we propose a new technique based on paral...
Kaidi Zhao, Bing Liu, Thomas M. Tirpak, Andreas Sc...
EDM
2009
175views Data Mining» more  EDM 2009»
13 years 7 months ago
Detecting Symptoms of Low Performance Using Production Rules
E-Learning systems offer students innovative and attractive ways of learning through augmentation or substitution of traditional lectures and exercises with online learning materia...
Javier Bravo Agapito, Alvaro Ortigosa
FPL
2005
Springer
119views Hardware» more  FPL 2005»
14 years 3 months ago
Real-Time Feature Extraction for High Speed Networks
With the onset of Gigabit networks, current generation networking components will soon be insufficient for numerous reasons: most notably because existing methods cannot support h...
David Nguyen, Gokhan Memik, Seda Ogrenci Memik, Al...
ISMIS
2005
Springer
14 years 3 months ago
Learning the Daily Model of Network Traffic
Abstract. Anomaly detection is based on profiles that represent normal behaviour of users, hosts or networks and detects attacks as significant deviations from these profiles. In t...
Costantina Caruso, Donato Malerba, Davide Papagni