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98
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ICDM
2007
IEEE
170views Data Mining» more  ICDM 2007»
15 years 6 months ago
Consensus Clusterings
In this paper we address the problem of combining multiple clusterings without access to the underlying features of the data. This process is known in the literature as clustering...
Nam Nguyen, Rich Caruana
92
Voted
ICDM
2009
IEEE
110views Data Mining» more  ICDM 2009»
15 years 7 months ago
Projective Clustering Ensembles
Recent advances in data clustering concern clustering ensembles and projective clustering methods, each addressing different issues in clustering problems. In this paper, we consi...
Francesco Gullo, Carlotta Domeniconi, Andrea Tagar...
CIKM
2009
Springer
15 years 7 months ago
Fragment-based clustering ensembles
Clustering ensembles combine different clustering solutions into a single robust and stable one. Most of existing methods become highly time-consuming when the data size turns to ...
Ou Wu, Mingliang Zhu, Weiming Hu
144
Voted
SIGMOD
2011
ACM
269views Database» more  SIGMOD 2011»
14 years 3 months ago
Advancing data clustering via projective clustering ensembles
Projective Clustering Ensembles (PCE) are a very recent advance in data clustering research which combines the two powerful tools of clustering ensembles and projective clustering...
Francesco Gullo, Carlotta Domeniconi, Andrea Tagar...
PKDD
2010
Springer
146views Data Mining» more  PKDD 2010»
14 years 10 months ago
Nonparametric Bayesian Clustering Ensembles
Forming consensus clusters from multiple input clusterings can improve accuracy and robustness. Current clustering ensemble methods require specifying the number of consensus clust...
Pu Wang, Carlotta Domeniconi, Kathryn Blackmond La...