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» Learning from Multiple Sources of Inaccurate Data
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BIBE
2005
IEEE
14 years 2 months ago
Using Data Mining Techniques to Learn Layouts of Flat-File Biological Datasets
One of the major problems in biological data integration is that many data sources are stored as flat-files, with a variety of different layouts. Integrating data from such sour...
Kaushik Sinha, Xuan Zhang, Ruoming Jin, Gagan Agra...
DEXAW
2002
IEEE
107views Database» more  DEXAW 2002»
14 years 1 months ago
Semi-Automated Extraction of Ontological Knowledge from XML Datasources
In the paper we present a methodology for the semiautomated extraction of ontological knowledge from XML data sources in a given domain. We consider an interconnection scenario ov...
Silvana Castano, Valeria De Antonellis, Sabrina De...
CHI
2009
ACM
14 years 9 months ago
Learning to predict information needs: context-aware display as a cognitive aid and an assessment tool
We discuss the problem of assessing and aiding user performance in dynamic tasks that require rapid selection among multiple information sources. Motivated by research in human se...
Bradley C. Love, Matt Jones, Marc T. Tomlinson, Mi...
JMLR
2010
152views more  JMLR 2010»
13 years 3 months ago
The SHOGUN Machine Learning Toolbox
We have developed a machine learning toolbox, called SHOGUN, which is designed for unified large-scale learning for a broad range of feature types and learning settings. It offers...
Sören Sonnenburg, Gunnar Rätsch, Sebasti...
CVPR
2009
IEEE
15 years 3 months ago
Learning to Track with Multiple Observers
We propose a novel approach to designing algorithms for object tracking based on fusing multiple observation models. As the space of possible observation models is too large for...
Björn Stenger, Roberto Cipolla, Thomas Woodle...