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SDM
2007
SIAM
122views Data Mining» more  SDM 2007»
13 years 10 months ago
Incremental Spectral Clustering With Application to Monitoring of Evolving Blog Communities
In recent years, spectral clustering method has gained attentions because of its superior performance compared to other traditional clustering algorithms such as K-means algorithm...
Huazhong Ning, Wei Xu, Yun Chi, Yihong Gong, Thoma...
KDD
2001
ACM
181views Data Mining» more  KDD 2001»
14 years 9 months ago
Co-clustering documents and words using bipartite spectral graph partitioning
Both document clustering and word clustering are well studied problems. Most existing algorithms cluster documents and words separately but not simultaneously. In this paper we pr...
Inderjit S. Dhillon
KDD
2004
ACM
190views Data Mining» more  KDD 2004»
14 years 9 months ago
Kernel k-means: spectral clustering and normalized cuts
Kernel k-means and spectral clustering have both been used to identify clusters that are non-linearly separable in input space. Despite significant research, these methods have re...
Inderjit S. Dhillon, Yuqiang Guan, Brian Kulis
BMCBI
2010
136views more  BMCBI 2010»
13 years 8 months ago
SCPS: a fast implementation of a spectral method for detecting protein families on a genome-wide scale
Background: An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed...
Tamás Nepusz, Rajkumar Sasidharan, Alberto ...
DILS
2008
Springer
13 years 10 months ago
Semi Supervised Spectral Clustering for Regulatory Module Discovery
We propose a novel semi-supervised clustering method for the task of gene regulatory module discovery. The technique uses data on dna binding as prior knowledge to guide the proces...
Alok Mishra, Duncan Gillies