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EWSN
2008
Springer
15 years 9 months ago
Spatiotemporal Anomaly Detection in Gas Monitoring Sensor Networks
In this paper3 , we use Bayesian Networks as a means for unsupervised learning and anomaly (event) detection in gas monitoring sensor networks for underground coal mines. We show t...
X. Rosalind Wang, Joseph T. Lizier, Oliver Obst, M...
PAKDD
2009
ACM
120views Data Mining» more  PAKDD 2009»
15 years 7 months ago
Detecting Link Hijacking by Web Spammers.
Abstract. Since current search engines employ link-based ranking algorithms as an important tool to decide a ranking of sites, Web spammers are making a significant effort to man...
Masaru Kitsuregawa, Masashi Toyoda, Young-joo Chun...
SDM
2009
SIAM
124views Data Mining» more  SDM 2009»
15 years 7 months ago
Non-parametric Information-Theoretic Measures of One-Dimensional Distribution Functions from Continuous Time Series.
We study non-parametric measures for the problem of comparing distributions, which arise in anomaly detection for continuous time series. Non-parametric measures take two distribu...
Ali Dasdan, Paolo D'Alberto
SDM
2009
SIAM
173views Data Mining» more  SDM 2009»
15 years 7 months ago
Discretized Spatio-Temporal Scan Window.
The focus of this paper is the discovery of anomalous spatio-temporal windows. We propose a Discretized SpatioTemporal Scan Window approach to address the question of how we can t...
Aryya Gangopadhyay, Seyed H. Mohammadi, Vandana Pu...
SDM
2009
SIAM
112views Data Mining» more  SDM 2009»
15 years 7 months ago
A Re-evaluation of the Over-Searching Phenomenon in Inductive Rule Learning.
Most commonly used inductive rule learning algorithms employ a hill-climbing search, whereas local pattern discovery algorithms employ exhaustive search. In this paper, we evaluat...
Frederik Janssen, Johannes Fürnkranz
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