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» Applying Grid Technologies to Distributed Data Mining
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CIKM
2005
Springer
14 years 1 months ago
Mining officially unrecognized side effects of drugs by combining web search and machine learning
We consider the problem of finding officially unrecognized side effects of drugs. By submitting queries to the Web involving a given drug name, it is possible to retrieve pages co...
Carlo Curino, Yuanyuan Jia, Bruce Lambert, Patrici...
BMCBI
2005
150views more  BMCBI 2005»
13 years 8 months ago
Discover protein sequence signatures from protein-protein interaction data
Background: The development of high-throughput technologies such as yeast two-hybrid systems and mass spectrometry technologies has made it possible to generate large protein-prot...
Jianwen Fang, Ryan J. Haasl, Yinghua Dong, Gerald ...
KDD
2010
ACM
310views Data Mining» more  KDD 2010»
13 years 12 months ago
An integrated machine learning approach to stroke prediction
Stroke is the third leading cause of death and the principal cause of serious long-term disability in the United States. Accurate prediction of stroke is highly valuable for early...
Aditya Khosla, Yu Cao, Cliff Chiung-Yu Lin, Hsu-Ku...
KDD
2008
ACM
183views Data Mining» more  KDD 2008»
14 years 8 months ago
A bayesian mixture model with linear regression mixing proportions
Classic mixture models assume that the prevalence of the various mixture components is fixed and does not vary over time. This presents problems for applications where the goal is...
Xiuyao Song, Chris Jermaine, Sanjay Ranka, John Gu...
OTM
2007
Springer
14 years 2 months ago
Semantically Resolving Type Mismatches in Scientific Workflows
Scientists are increasingly utilizing Grids to manage large data sets and execute scientific experiments on distributed resources. Scientific workflows are used as means for modeli...
Kheiredine Derouiche, Denis A. Nicole