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BMCBI
2010
151views more  BMCBI 2010»
13 years 10 months ago
Data reduction for spectral clustering to analyze high throughput flow cytometry data
Background: Recent biological discoveries have shown that clustering large datasets is essential for better understanding biology in many areas. Spectral clustering in particular ...
Habil Zare, Parisa Shooshtari, Arvind Gupta, Ryan ...
TCBB
2010
136views more  TCBB 2010»
13 years 8 months ago
Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data
— The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses ...
Oliver Rübel, Gunther H. Weber, Min-Yu Huang,...
KDD
2002
ACM
138views Data Mining» more  KDD 2002»
14 years 10 months ago
Learning to match and cluster large high-dimensional data sets for data integration
Part of the process of data integration is determining which sets of identifiers refer to the same real-world entities. In integrating databases found on the Web or obtained by us...
William W. Cohen, Jacob Richman
SIGMOD
2008
ACM
107views Database» more  SIGMOD 2008»
14 years 10 months ago
Outlier-robust clustering using independent components
How can we efficiently find a clustering, i.e. a concise description of the cluster structure, of a given data set which contains an unknown number of clusters of different shape ...
Christian Böhm, Christos Faloutsos, Claudia P...
CIDM
2009
IEEE
14 years 3 months ago
An architecture and algorithms for multi-run clustering
—This paper addresses two main challenges for clustering which require extensive human effort: selecting appropriate parameters for an arbitrary clustering algorithm and identify...
Rachsuda Jiamthapthaksin, Christoph F. Eick, Vadee...