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» Predicting labels for dyadic data
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WSDM
2010
ACM
254views Data Mining» more  WSDM 2010»
14 years 7 months ago
Learning Influence Probabilities In Social Networks
Recently, there has been tremendous interest in the phenomenon of influence propagation in social networks. The studies in this area assume they have as input to their problems a ...
Amit Goyal 0002, Francesco Bonchi, Laks V. S. Laks...
SIGSOFT
2009
ACM
14 years 10 months ago
Fair and balanced?: bias in bug-fix datasets
Software engineering researchers have long been interested in where and why bugs occur in code, and in predicting where they might turn up next. Historical bug-occurence data has ...
Christian Bird, Adrian Bachmann, Eirik Aune, John ...
BMCBI
2010
147views more  BMCBI 2010»
13 years 10 months ago
Indirect two-sided relative ranking: a robust similarity measure for gene expression data
Background: There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunatel...
Louis Licamele, Lise Getoor
BMCBI
2010
110views more  BMCBI 2010»
13 years 10 months ago
Towards the systematic discovery of signal transduction networks using phosphorylation dynamics data
Background: Phosphorylation is a ubiquitous and fundamental regulatory mechanism that controls signal transduction in living cells. The number of identified phosphoproteins and th...
Haruna Imamura, Nozomu Yachie, Rintaro Saito, Yasu...
BMCBI
2008
108views more  BMCBI 2008»
13 years 10 months ago
Supervised Lowess normalization of comparative genome hybridization data - application to lactococcal strain comparisons
Background: Array-based comparative genome hybridization (aCGH) is commonly used to determine the genomic content of bacterial strains. Since prokaryotes in general have less cons...
Sacha A. F. T. van Hijum, Richard J. S. Baerends, ...