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KDD
2010
ACM
326views Data Mining» more  KDD 2010»
13 years 5 months ago
Document clustering via dirichlet process mixture model with feature selection
One essential issue of document clustering is to estimate the appropriate number of clusters for a document collection to which documents should be partitioned. In this paper, we ...
Guan Yu, Ruizhang Huang, Zhaojun Wang
CGF
2010
171views more  CGF 2010»
13 years 4 months ago
Efficient Mean-shift Clustering Using Gaussian KD-Tree
Mean shift is a popular approach for data clustering, however, the high computational complexity of the mean shift procedure limits its practical applications in high dimensional ...
Chunxia Xiao, Meng Liu
SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
12 years 10 months ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
KDD
2005
ACM
118views Data Mining» more  KDD 2005»
14 years 8 months ago
On the use of linear programming for unsupervised text classification
We propose a new algorithm for dimensionality reduction and unsupervised text classification. We use mixture models as underlying process of generating corpus and utilize a novel,...
Mark Sandler
GIS
2008
ACM
14 years 8 months ago
Mining user similarity based on location history
The pervasiveness of location-acquisition technologies (GPS, GSM networks, etc.) enable people to conveniently log the location histories they visited with spatio-temporal data. T...
Quannan Li, Yu Zheng, Xing Xie, Yukun Chen, Wenyu ...