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SDM
2009
SIAM
173views Data Mining» more  SDM 2009»
16 years 1 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
144views Data Mining» more  SDM 2009»
16 years 1 months ago
CORE: Nonparametric Clustering of Large Numeric Databases.
Current clustering techniques are able to identify arbitrarily shaped clusters in the presence of noise, but depend on carefully chosen model parameters. The choice of model param...
Andrej Taliun, Arturas Mazeika, Michael H. Bö...
SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
16 years 1 months ago
On the Comparison of Relative Clustering Validity Criteria.
Many different relative clustering validity criteria exist that are very useful in practice as quantitative measures for evaluating the quality of data partitions, and new criter...
Lucas Vendramin, Ricardo J. G. B. Campello, Eduard...
SDM
2009
SIAM
112views Data Mining» more  SDM 2009»
16 years 1 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
SDM
2009
SIAM
176views Data Mining» more  SDM 2009»
16 years 1 months ago
Constraint-Based Subspace Clustering.
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
Élisa Fromont, Adriana Prado, Céline...
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