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» Massive Data Pre-Processing with a Cluster Based Approach
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PAISI
2010
Springer
14 years 9 months ago
Efficient Privacy Preserving K-Means Clustering
Abstract. This paper introduces an efficient privacy-preserving protocol for distributed K-means clustering over an arbitrary partitioned data, shared among N parties. Clustering i...
Maneesh Upmanyu, Anoop M. Namboodiri, Kannan Srina...
PRL
2006
77views more  PRL 2006»
14 years 11 months ago
Wavelet based approach to cluster analysis. Application on low dimensional data sets
In this paper, we present a wavelet based approach which tries to automatically find the number of clusters present in a data set, along with their position and statistical proper...
Xavier Otazu, Oriol Pujol
ICDM
2002
IEEE
122views Data Mining» more  ICDM 2002»
15 years 4 months ago
Using Category-Based Adherence to Cluster Market-Basket Data
In this paper, we devise an efficient algorithm for clustering market-basket data. Different from those of the traditional data, the features of market-basket data are known to b...
Ching-Huang Yun, Kun-Ta Chuang, Ming-Syan Chen
ICDE
2012
IEEE
224views Database» more  ICDE 2012»
13 years 2 months ago
Exploiting Common Subexpressions for Cloud Query Processing
—Many companies now routinely run massive data analysis jobs – expressed in some scripting language – on large clusters of low-end servers. Many analysis scripts are complex ...
Yasin N. Silva, Paul-Ake Larson, Jingren Zhou
DAGM
2008
Springer
15 years 1 months ago
Boosting for Model-Based Data Clustering
In this paper a novel and generic approach for model-based data clustering in a boosting framework is presented. This method uses the forward stagewise additive modeling to learn t...
Amir Saffari, Horst Bischof