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» A Genetic Algorithm for Clustering on Very Large Data Sets
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ALMOB
2007
74views more  ALMOB 2007»
13 years 7 months ago
Evaluating deterministic motif significance measures in protein databases
Background: Assessing the outcome of motif mining algorithms is an essential task, as the number of reported motifs can be very large. Significance measures play a central role in...
Pedro Gabriel Ferreira, Paulo J. Azevedo
KDD
2012
ACM
194views Data Mining» more  KDD 2012»
11 years 10 months ago
A sparsity-inducing formulation for evolutionary co-clustering
Traditional co-clustering methods identify block structures from static data matrices. However, the data matrices in many applications are dynamic; that is, they evolve smoothly o...
Shuiwang Ji, Wenlu Zhang, Jun Liu
EDBT
2010
ACM
155views Database» more  EDBT 2010»
14 years 2 months ago
Reducing metadata complexity for faster table summarization
Since the visualization real estate puts stringent constraints on how much data can be presented to the users at once, table summarization is an essential tool in helping users qu...
K. Selçuk Candan, Mario Cataldi, Maria Luis...
KDD
2004
ACM
118views Data Mining» more  KDD 2004»
14 years 8 months ago
Parallel computation of high dimensional robust correlation and covariance matrices
The computation of covariance and correlation matrices are critical to many data mining applications and processes. Unfortunately the classical covariance and correlation matrices...
James Chilson, Raymond T. Ng, Alan Wagner, Ruben H...
KDD
2009
ACM
169views Data Mining» more  KDD 2009»
14 years 8 months ago
COA: finding novel patents through text analysis
In recent years, the number of patents filed by the business enterprises in the technology industry are growing rapidly, thus providing unprecedented opportunities for knowledge d...
Mohammad Al Hasan, W. Scott Spangler, Thomas D. Gr...