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139
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EWCBR
2006
Springer
15 years 7 months ago
Unsupervised Feature Selection for Text Data
Feature selection for unsupervised tasks is particularly challenging, especially when dealing with text data. The increase in online documents and email communication creates a nee...
Nirmalie Wiratunga, Robert Lothian, Stewart Massie
140
Voted
ICDM
2007
IEEE
129views Data Mining» more  ICDM 2007»
15 years 9 months ago
Semi-supervised Clustering Using Bayesian Regularization
Text clustering is most commonly treated as a fully automated task without user supervision. However, we can improve clustering performance using supervision in the form of pairwi...
Zuobing Xu, Ram Akella, Mike Ching, Renjie Tang
144
Voted
ICDM
2006
IEEE
152views Data Mining» more  ICDM 2006»
15 years 9 months ago
Application of Graph-based Data Mining to Metabolic Pathways
We present a method for finding biologically meaningful patterns on metabolic pathways using the SUBDUE graph-based relational learning system. A huge amount of biological data t...
Chang Hun You, Lawrence B. Holder, Diane J. Cook
ICIP
2008
IEEE
15 years 10 months ago
Learning efficient codes for 3D face recognition
Face representation based on the Visual Codebook becomes popular because of its excellent recognition performance, in which the critical problem is how to learn the most efficien...
Cheng Zhong, Zhenan Sun, Tieniu Tan
127
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ICDM
2006
IEEE
100views Data Mining» more  ICDM 2006»
15 years 9 months ago
Meta Clustering
Clustering is ill-defined. Unlike supervised learning where labels lead to crisp performance criteria such as accuracy and squared error, clustering quality depends on how the cl...
Rich Caruana, Mohamed Farid Elhawary, Nam Nguyen, ...