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» Detecting anomalies in data streams using statecharts
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FLAIRS
2008
15 years 2 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»
14 years 2 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
14 years 9 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
15 years 6 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
15 years 4 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...