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» CURE: An Efficient Clustering Algorithm for Large Databases
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15 years 5 months ago
Genes, Themes, and Microarrays: Using Information Retrieval for Large-Scale Gene Analysis
The immensevolumeof data resulting from DNAmicroarray experiments, accompaniedby an increase in the numberof publications discussing gene-related discoveries, presents a majordata...
Hagit Shatkay, Stephen Edwards, W. John Wilbur, Ma...
121
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NN
2006
Springer
113views Neural Networks» more  NN 2006»
15 years 3 months ago
Large-scale data exploration with the hierarchically growing hyperbolic SOM
We introduce the Hierarchically Growing Hyperbolic Self-Organizing Map (H2 SOM) featuring two extensions of the HSOM (hyperbolic SOM): (i) a hierarchically growing variant that al...
Jörg Ontrup, Helge Ritter
148
Voted
WWW
2004
ACM
16 years 4 months ago
Web image learning for searching semantic concepts in image databases
Without textual descriptions or label information of images, searching semantic concepts in image databases is still a very challenging task. While automatic annotation techniques...
Chu-Hong Hoi, Michael R. Lyu
JPDC
2008
92views more  JPDC 2008»
15 years 3 months ago
Techniques for pipelined broadcast on ethernet switched clusters
By splitting a large broadcast message into segments and broadcasting the segments in a pipelined fashion, pipelined broadcast can achieve high performance in many systems. In thi...
Pitch Patarasuk, Xin Yuan, Ahmad Faraj
130
Voted
EDBT
2004
ACM
142views Database» more  EDBT 2004»
16 years 3 months ago
Iterative Incremental Clustering of Time Series
We present a novel anytime version of partitional clustering algorithm, such as k-Means and EM, for time series. The algorithm works by leveraging off the multi-resolution property...
Jessica Lin, Michail Vlachos, Eamonn J. Keogh, Dim...