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WEBI
2004
Springer
15 years 12 months ago
Co-training with a Single Natural Feature Set Applied to Email Classification
When dealing with information overload from the Internet, such as the classification of Web pages and the filtering of email spam, a new technique called cotraining has been shown...
Jason Chan, Irena Koprinska, Josiah Poon
CLOR
2006
15 years 10 months ago
A Discriminative Framework for Texture and Object Recognition Using Local Image Features
This chapter presents an approach for texture and object recognition that uses scale- or affine-invariant local image features in combination with a discriminative classifier. Text...
Svetlana Lazebnik, Cordelia Schmid, Jean Ponce
FLAIRS
2008
15 years 9 months ago
A Semantic Feature for Verbal Predicate and Semantic Role Labeling Using SVMs
This paper shows that semantic role labeling is a consequence of accurate verbal predicate labeling. In doing so, the paper presents a novel type of semantic feature for verbal pr...
Hansen A. Schwartz, Fernando Gomez, Christopher Mi...
181
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SDM
2008
SIAM
133views Data Mining» more  SDM 2008»
15 years 8 months ago
A RELIEF Based Feature Extraction Algorithm
RELIEF is considered one of the most successful algorithms for assessing the quality of features due to its simplicity and effectiveness. It has been recently proved that RELIEF i...
Yijun Sun, Dapeng Wu
ADCS
2004
15 years 8 months ago
Co-Training on Textual Documents with a Single Natural Feature Set
Co-training is a semi-supervised technique that allows classifiers to learn with fewer labelled documents by taking advantage of the more abundant unclassified documents. However, ...
Jason Chan, Irena Koprinska, Josiah Poon