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KDD
2009
ACM
611views Data Mining» more  KDD 2009»
14 years 8 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
DASFAA
2007
IEEE
190views Database» more  DASFAA 2007»
14 years 2 months ago
Clustering Moving Objects in Spatial Networks
Advances in wireless networks and positioning technologies (e.g., GPS) have enabled new data management applications that monitor moving objects. In such new applications, realtime...
Jidong Chen, Caifeng Lai, Xiaofeng Meng, Jianliang...
PAMI
1998
88views more  PAMI 1998»
13 years 7 months ago
Large-Scale Parallel Data Clustering
—Algorithmic enhancements are described that enable large computational reduction in mean square-error data clustering. These improvements are incorporated into a parallel data-c...
Dan Judd, Philip K. McKinley, Anil K. Jain
ICDE
2009
IEEE
202views Database» more  ICDE 2009»
14 years 9 months ago
Tracking High Quality Clusters over Uncertain Data Streams
Recently, data mining over uncertain data streams has attracted a lot of attentions because of the widely existed imprecise data generated from a variety of streaming applications....
Chen Zhang, Ming Gao, Aoying Zhou
BMCBI
2008
142views more  BMCBI 2008»
13 years 8 months ago
Microarray data mining: A novel optimization-based approach to uncover biologically coherent structures
Background: DNA microarray technology allows for the measurement of genome-wide expression patterns. Within the resultant mass of data lies the problem of analyzing and presenting...
Meng Piao Tan, Erin N. Smith, James R. Broach, Chr...