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» Accelerated EM-based clustering of large data sets
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KDD
2002
ACM
155views Data Mining» more  KDD 2002»
14 years 5 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
LREC
2008
129views Education» more  LREC 2008»
13 years 6 months ago
Spectral Clustering for a Large Data Set by Reducing the Similarity Matrix Size
Spectral clustering is a powerful clustering method for document data set. However, spectral clustering needs to solve an eigenvalue problem of the matrix converted from the simil...
Hiroyuki Shinnou, Minoru Sasaki
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
14 years 5 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
ICDM
2002
IEEE
159views Data Mining» more  ICDM 2002»
13 years 10 months ago
O-Cluster: Scalable Clustering of Large High Dimensional Data Sets
Clustering large data sets of high dimensionality has always been a serious challenge for clustering algorithms. Many recently developed clustering algorithms have attempted to ad...
Boriana L. Milenova, Marcos M. Campos
ICDM
2003
IEEE
138views Data Mining» more  ICDM 2003»
13 years 10 months ago
PixelMaps: A New Visual Data Mining Approach for Analyzing Large Spatial Data Sets
PixelMaps are a new pixel-oriented visual data mining technique for large spatial datasets. They combine kerneldensity-based clustering with pixel-oriented displays to emphasize c...
Daniel A. Keim, Christian Panse, Mike Sips, Stephe...