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SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
16 years 3 months ago
On the Comparison of Relative Clustering Validity Criteria.
Many different relative clustering validity criteria exist that are very useful in practice as quantitative measures for evaluating the quality of data partitions, and new criter...
Lucas Vendramin, Ricardo J. G. B. Campello, Eduard...
SDM
2009
SIAM
176views Data Mining» more  SDM 2009»
16 years 3 months ago
Constraint-Based Subspace Clustering.
In high dimensional data, the general performance of traditional clustering algorithms decreases. This is partly because the similarity criterion used by these algorithms becomes ...
Élisa Fromont, Adriana Prado, Céline...
SDM
2009
SIAM
193views Data Mining» more  SDM 2009»
16 years 3 months ago
Agglomerative Mean-Shift Clustering via Query Set Compression.
Mean-Shift (MS) is a powerful non-parametric clustering method. Although good accuracy can be achieved, its computational cost is particularly expensive even on moderate data sets...
Xiaotong Yuan, Bao-Gang Hu, Ran He
SDM
2009
SIAM
117views Data Mining» more  SDM 2009»
16 years 3 months ago
Spatially Cost-Sensitive Active Learning.
In active learning, one attempts to maximize classifier performance for a given number of labeled training points by allowing the active learning algorithm to choose which points...
Alexander Liu, Goo Jun, Joydeep Ghosh
SDM
2009
SIAM
331views Data Mining» more  SDM 2009»
16 years 3 months ago
Privacy Preservation in Social Networks with Sensitive Edge Weights.
With the development of emerging social networks, such as Facebook and MySpace, security and privacy threats arising from social network analysis bring a risk of disclosure of con...
Jie Wang, Jinze Liu, Jun Zhang, Lian Liu
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