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SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
15 years 8 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...
80
Voted
SDM
2009
SIAM
176views Data Mining» more  SDM 2009»
15 years 8 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»
15 years 8 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
96
Voted
SDM
2009
SIAM
117views Data Mining» more  SDM 2009»
15 years 8 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
100
Voted
WWW
2010
ACM
15 years 5 months ago
Find me if you can: improving geographical prediction with social and spatial proximity
Geography and social relationships are inextricably intertwined; the people we interact with on a daily basis almost always live near us. As people spend more time online, data re...
Lars Backstrom, Eric Sun, Cameron Marlow
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