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...
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...
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...
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...
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...