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» Scaling Clustering Algorithms to Large Databases
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ICDE
2006
IEEE
167views Database» more  ICDE 2006»
14 years 9 months ago
Mining Shifting-and-Scaling Co-Regulation Patterns on Gene Expression Profiles
In this paper, we propose a new model for coherent clustering of gene expression data called reg-cluster. The proposed model allows (1) the expression profiles of genes in a clust...
Xin Xu, Ying Lu, Anthony K. H. Tung, Wei Wang 0010
SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
14 years 5 months ago
GAD: General Activity Detection for Fast Clustering on Large Data.
In this paper, we propose GAD (General Activity Detection) for fast clustering on large scale data. Within this framework we design a set of algorithms for different scenarios: (...
Jiawei Han, Liangliang Cao, Sangkyum Kim, Xin Jin,...
IPPS
2007
IEEE
14 years 2 months ago
An Energy-Efficient Framework for Large-Scale Parallel Storage Systems
Huge energy consumption has become a critical bottleneck for further applying large-scale cluster systems to build new data centers. Among various components of a data center, sto...
Ziliang Zong, Matt Briggs, Nick O'Connor, Xiao Qin
CONCURRENCY
2008
84views more  CONCURRENCY 2008»
13 years 8 months ago
Dynamic allocation in a self-scaling cluster database
Abstract. Database systems have been vital for all forms of data processing for a long time. In recent years, the amount of processed data has been growing dramatically, even in sm...
Tilmann Rabl, Marc Pfeffer, Harald Kosch
EUROPAR
1999
Springer
14 years 21 days ago
Parallel k/h-Means Clustering for Large Data Sets
This paper describes the realization of a parallel version of the k/h-means clustering algorithm. This is one of the basic algorithms used in a wide range of data mining tasks. We ...
Kilian Stoffel, Abdelkader Belkoniene