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SIGMOD
2011
ACM
269views Database» more  SIGMOD 2011»
14 years 9 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...
DMIN
2006
146views Data Mining» more  DMIN 2006»
15 years 7 months ago
A Comparison of Two Document Clustering Approaches for Clustering Medical Documents
Medical data is often presented as free text in the form of medical reports. Such documents contain important information about patients, disease progression and management, but ar...
Fathi H. Saad, Beatriz de la Iglesia, Duncan G. Be...
KDD
2002
ACM
155views Data Mining» more  KDD 2002»
16 years 6 months ago
SyMP: an efficient clustering approach to identify clusters of arbitrary shapes in large data sets
We propose a new clustering algorithm, called SyMP, which is based on synchronization of pulse-coupled oscillators. SyMP represents each data point by an Integrate-and-Fire oscill...
Hichem Frigui
177
Voted
ICML
2007
IEEE
16 years 7 months ago
A dependence maximization view of clustering
We propose a family of clustering algorithms based on the maximization of dependence between the input variables and their cluster labels, as expressed by the Hilbert-Schmidt Inde...
Le Song, Alexander J. Smola, Arthur Gretton, Karst...
WILF
2007
Springer
98views Fuzzy Logic» more  WILF 2007»
16 years 11 days ago
Possibilistic Clustering in Feature Space
In this paper we propose the Possibilistic C-Means in Feature Space and the One-Cluster Possibilistic C-Means in Feature Space algorithms which are kernel methods for clustering in...
Maurizio Filippone, Francesco Masulli, Stefano Rov...