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110
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ICML
2009
IEEE
16 years 4 months ago
Bayesian clustering for email campaign detection
We discuss the problem of clustering elements according to the sources that have generated them. For elements that are characterized by independent binary attributes, a closedform...
Peter Haider, Tobias Scheffer
129
Voted
AUSDM
2007
Springer
101views Data Mining» more  AUSDM 2007»
15 years 7 months ago
Exploratory Multilevel Hot Spot Analysis: Australian Taxation Office Case Study
Population based real-life datasets often contain smaller clusters of unusual sub-populations. While these clusters, called `hot spots', are small and sparse, they are usuall...
Denny, Graham J. Williams, Peter Christen
IJPRAI
2008
144views more  IJPRAI 2008»
15 years 3 months ago
Unsupervised Learning of a Hierarchy of Topological Maps Using Omnidirectional Images
unsupervised construction of topological maps, which provide an abstraction of the environment in terms of visual aspects. An unsupervised clustering algorithm is used to represent...
Ales Stimec, Matjaz Jogan, Ales Leonardis
123
Voted
ECML
2007
Springer
15 years 9 months ago
Spectral Clustering and Embedding with Hidden Markov Models
Abstract. Clustering has recently enjoyed progress via spectral methods which group data using only pairwise affinities and avoid parametric assumptions. While spectral clustering ...
Tony Jebara, Yingbo Song, Kapil Thadani
120
Voted
GD
2005
Springer
15 years 9 months ago
Drawing Clustered Graphs in Three Dimensions
Clustered graph is a very useful model for drawing large and complex networks. This paper presents a new method for drawing clustered graphs in three dimensions. The method uses a ...
Joshua Wing Kei Ho, Seok-Hee Hong