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» Learning Classifiers from Semantically Heterogeneous Data
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KDD
2009
ACM
211views Data Mining» more  KDD 2009»
14 years 10 months ago
Address standardization with latent semantic association
Address standardization is a very challenging task in data cleansing. To provide better customer relationship management and business intelligence for customer-oriented cooperates...
Honglei Guo, Huijia Zhu, Zhili Guo, Xiaoxun Zhang,...
BMCBI
2008
112views more  BMCBI 2008»
13 years 10 months ago
A simplified approach to disulfide connectivity prediction from protein sequences
Background: Prediction of disulfide bridges from protein sequences is useful for characterizing structural and functional properties of proteins. Several methods based on differen...
Marc Vincent, Andrea Passerini, Matthieu Labb&eacu...
IEEEMM
2002
291views more  IEEEMM 2002»
13 years 10 months ago
Semantic Annotation of Sports Videos
ion when we annotate content. This therefore requires us to investigate and model video semantics. Because of the type and volume of data, general-purpose approaches are likely to ...
Jürgen Assfalg, Marco Bertini, Carlo Colombo,...
KDD
2002
ACM
108views Data Mining» more  KDD 2002»
14 years 10 months ago
Incremental Machine Learning to Reduce Biochemistry Lab Costs in the Search for Drug Discovery
This paper promotes the use of supervised machine learning in laboratory settings where chemists have a large number of samples to test for some property, and are interested in id...
George Forman
ECCV
2010
Springer
14 years 15 days ago
Learning Shape Segmentation Using Constrained Spectral Clustering and Probabilistic Label Transfer
We propose a spectral learning approach to shape segmentation. The method is composed of a constrained spectral clustering algorithm that is used to supervise the segmentation of a...