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PODS
2008
ACM
159views Database» more  PODS 2008»
14 years 5 months ago
Approximation algorithms for clustering uncertain data
There is an increasing quantity of data with uncertainty arising from applications such as sensor network measurements, record linkage, and as output of mining algorithms. This un...
Graham Cormode, Andrew McGregor
CIKM
2006
Springer
13 years 7 months ago
Efficiently clustering transactional data with weighted coverage density
In this paper, we propose a fast, memory-efficient, and scalable clustering algorithm for analyzing transactional data. Our approach has three unique features. First, we use the c...
Hua Yan, Keke Chen, Ling Liu
APBC
2004
164views Bioinformatics» more  APBC 2004»
13 years 7 months ago
Cluster Ensemble and Its Applications in Gene Expression Analysis
Huge amount of gene expression data have been generated as a result of the human genomic project. Clustering has been used extensively in mining these gene expression data to find...
Xiaohua Hu, Illhoi Yoo
BMCBI
2008
117views more  BMCBI 2008»
13 years 5 months ago
New resampling method for evaluating stability of clusters
Background: Hierarchical clustering is a widely applied tool in the analysis of microarray gene expression data. The assessment of cluster stability is a major challenge in cluste...
Irina Gana Dresen, Tanja Boes, Johannes Hüsin...
PVLDB
2008
107views more  PVLDB 2008»
13 years 4 months ago
Constrained locally weighted clustering
Data clustering is a difficult problem due to the complex and heterogeneous natures of multidimensional data. To improve clustering accuracy, we propose a scheme to capture the lo...
Hao Cheng, Kien A. Hua, Khanh Vu