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» Informative sampling for large unbalanced data sets
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126
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SIGIR
2006
ACM
15 years 9 months ago
Bias and the limits of pooling
Modern retrieval test collections are built through a process called pooling in which only a sample of the entire document set is judged for each topic. The idea behind pooling is...
Chris Buckley, Darrin Dimmick, Ian Soboroff, Ellen...
273
Voted
SDM
2011
SIAM
414views Data Mining» more  SDM 2011»
14 years 6 months ago
Clustered low rank approximation of graphs in information science applications
In this paper we present a fast and accurate procedure called clustered low rank matrix approximation for massive graphs. The procedure involves a fast clustering of the graph and...
Berkant Savas, Inderjit S. Dhillon
151
Voted
BMCBI
2007
157views more  BMCBI 2007»
15 years 3 months ago
Statistical learning of peptide retention behavior in chromatographic separations: a new kernel-based approach for computational
Background: High-throughput peptide and protein identification technologies have benefited tremendously from strategies based on tandem mass spectrometry (MS/MS) in combination wi...
Nico Pfeifer, Andreas Leinenbach, Christian G. Hub...
140
Voted
CIDR
2009
141views Algorithms» more  CIDR 2009»
15 years 4 months ago
Sailing the Information Ocean with Awareness of Currents: Discovery and Application of Source Dependence
The Web has enabled the availability of a huge amount of useful information, but has also eased the ability to spread false information and rumors across multiple sources, making ...
Laure Berti-Equille, Anish Das Sarma, Xin Dong, Am...
138
Voted
BMCBI
2005
246views more  BMCBI 2005»
15 years 3 months ago
ParPEST: a pipeline for EST data analysis based on parallel computing
Background: Expressed Sequence Tags (ESTs) are short and error-prone DNA sequences generated from the 5' and 3' ends of randomly selected cDNA clones. They provide an im...
Nunzio D'Agostino, Mario Aversano, Maria Luisa Chi...