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» Detecting anomalies in data streams using statecharts
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FLAIRS
2008
13 years 7 months ago
Distance Metric Learning for Conditional Anomaly Detection
Anomaly detection methods can be very useful in identifying unusual or interesting patterns in data. A recently proposed conditional anomaly detection framework extends anomaly de...
Michal Valko, Milos Hauskrecht
SDM
2011
SIAM
256views Data Mining» more  SDM 2011»
12 years 8 months ago
Temporal Structure Learning for Clustering Massive Data Streams in Real-Time
This paper describes one of the first attempts to model the temporal structure of massive data streams in real-time using data stream clustering. Recently, many data stream clust...
Michael Hahsler, Margaret H. Dunham
IPPS
2010
IEEE
13 years 3 months ago
Distributed monitoring of conditional entropy for anomaly detection in streams
In this work we consider the problem of monitoring information streams for anomalies in a scalable and efficient manner. We study the problem in the context of network streams wher...
Chrisil Arackaparambil, Sergey Bratus, Joshua Brod...
ISMIS
2009
Springer
13 years 12 months ago
Novelty Detection from Evolving Complex Data Streams with Time Windows
Abstract. Novelty detection in data stream mining denotes the identification of new or unknown situations in a stream of data elements flowing continuously in at rapid rate. This...
Michelangelo Ceci, Annalisa Appice, Corrado Loglis...
SAC
2010
ACM
13 years 10 months ago
Data stream anomaly detection through principal subspace tracking
We consider the problem of anomaly detection in multiple co-evolving data streams. In this paper, we introduce FRAHST (Fast Rank-Adaptive row-Householder Subspace Tracking). It au...
Pedro Henriques dos Santos Teixeira, Ruy Luiz Mili...