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» Mining Multiple Large Databases
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KDD
2009
ACM
227views Data Mining» more  KDD 2009»
16 years 2 months ago
Efficiently learning the accuracy of labeling sources for selective sampling
Many scalable data mining tasks rely on active learning to provide the most useful accurately labeled instances. However, what if there are multiple labeling sources (`oracles...
Pinar Donmez, Jaime G. Carbonell, Jeff Schneider
KDD
2008
ACM
213views Data Mining» more  KDD 2008»
16 years 2 months ago
Heterogeneous data fusion for alzheimer's disease study
Effective diagnosis of Alzheimer's disease (AD) is of primary importance in biomedical research. Recent studies have demonstrated that neuroimaging parameters are sensitive a...
Jieping Ye, Kewei Chen, Teresa Wu, Jing Li, Zheng ...
BMCBI
2005
106views more  BMCBI 2005»
15 years 1 months ago
Thesaurus-based disambiguation of gene symbols
Background: Massive text mining of the biological literature holds great promise of relating disparate information and discovering new knowledge. However, disambiguation of gene s...
Bob J. A. Schijvenaars, Barend Mons, Marc Weeber, ...
VLDB
2005
ACM
146views Database» more  VLDB 2005»
16 years 2 months ago
Adaptive website recommendations with AWESOME
Recommendations are crucial for the success of large websites. While there are many ways to determine recommendations, the relative quality of these recommenders depends on many fa...
Andreas Thor, Nick Golovin, Erhard Rahm
CVPR
2007
IEEE
16 years 4 months ago
Learning to Detect A Salient Object
We study visual attention by detecting a salient object in an input image. We formulate salient object detection as an image segmentation problem, where we separate the salient obj...
Tie Liu, Jian Sun, Nanning Zheng, Xiaoou Tang, Heu...