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» Data Clustering: A Review
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PAKDD
2009
ACM
123views Data Mining» more  PAKDD 2009»
14 years 1 months ago
Clustering with Lower Bound on Similarity
We propose a new method, called SimClus, for clustering with lower bound on similarity. Instead of accepting k the number of clusters to find, the alternative similarity-based app...
Mohammad Al Hasan, Saeed Salem, Benjarath Pupacdi,...
PAKDD
2000
ACM
124views Data Mining» more  PAKDD 2000»
14 years 19 days ago
Feature Selection for Clustering
In clustering, global feature selection algorithms attempt to select a common feature subset that is relevant to all clusters. Consequently, they are not able to identify individu...
Manoranjan Dash, Huan Liu
CSREASAM
2007
13 years 10 months ago
Survey of Supercomputer Cluster Security Issues
- The authors believe that providing security for supercomputer clusters is different from providing security for stand-alone PCs. The types of programs that supercomputer clusters...
George Markowsky, Linda Markowsky
SDM
2007
SIAM
117views Data Mining» more  SDM 2007»
13 years 10 months ago
Discriminating Subsequence Discovery for Sequence Clustering
In this paper, we explore the discriminating subsequencebased clustering problem. First, several effective optimization techniques are proposed to accelerate the sequence mining p...
Jianyong Wang, Yuzhou Zhang, Lizhu Zhou, George Ka...
CVPR
2008
IEEE
14 years 11 months ago
Correlational spectral clustering
We present a new method for spectral clustering with paired data based on kernel canonical correlation analysis, called correlational spectral clustering. Paired data are common i...
Matthew B. Blaschko, Christoph H. Lampert