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ICDM
2007
IEEE
149views Data Mining» more  ICDM 2007»
14 years 2 months ago
Solving Consensus and Semi-supervised Clustering Problems Using Nonnegative Matrix Factorization
Consensus clustering and semi-supervised clustering are important extensions of the standard clustering paradigm. Consensus clustering (also known as aggregation of clustering) ca...
Tao Li, Chris H. Q. Ding, Michael I. Jordan
SSDBM
2005
IEEE
218views Database» more  SSDBM 2005»
14 years 1 months ago
The "Best K" for Entropy-based Categorical Data Clustering
With the growing demand on cluster analysis for categorical data, a handful of categorical clustering algorithms have been developed. Surprisingly, to our knowledge, none has sati...
Keke Chen, Ling Liu
CCGRID
2007
IEEE
14 years 2 months ago
A Simulation Study of Data Partitioning Algorithms for Multiple Clusters
Abstract— Recently we proposed algorithms for concurrent execution on multiple clusters [9]. In this case, data partitioning is done at two levels; first, the data is distribute...
Chen Yu, Dan C. Marinescu, Howard Jay Siegel, John...
PRL
2008
135views more  PRL 2008»
13 years 7 months ago
A hierarchical clustering algorithm based on the Hungarian method
We propose a novel hierarchical clustering algorithm for data-sets in which only pairwise distances between the points are provided. The classical Hungarian method is an efficient...
Jacob Goldberger, Tamir Tassa
AI
2006
Springer
13 years 11 months ago
A New Profile Alignment Method for Clustering Gene Expression Data
We focus on clustering gene expression temporal profiles, and propose a novel, simple algorithm that is powerful enough to find an efficient distribution of genes over clusters. We...
Ataul Bari, Luis Rueda