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» Towards Using Fewer Features for Text Classification
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MLDM
2007
Springer
14 years 4 months ago
PE-PUC: A Graph Based PU-Learning Approach for Text Classification
This paper presents a novel solution for the problem of building text classifier using positive documents (P) and unlabeled documents (U). Here, the unlabeled documents are mixed w...
Shuang Yu, Chunping Li
ICASSP
2011
IEEE
13 years 1 months ago
Toward text message normalization: Modeling abbreviation generation
This paper describes a text normalization system for deletion-based abbreviations in informal text. We propose using statistical classifiers to learn the probability of deleting ...
Deana Pennell, Yang Liu
ICMLA
2009
13 years 7 months ago
Feature Extraction and Classification of EEG Signals for Rapid P300 Mind Spelling
The Mind Speller is a Brain-Computer Interface which enables subjects to spell text on a computer screen by detecting P300 Event-Related Potentials in their electroencephalograms....
Adrien Combaz, Nikolay V. Manyakov, Nikolay Chumer...
DMIN
2006
150views Data Mining» more  DMIN 2006»
13 years 11 months ago
Effect of Document Representation on the Performance of Medical Document Classification
Text classification in the medical domain is a real world problem with wide applicability. This paper investigates extensively the effect of text representation approaches on the p...
Fathi H. Saad, Beatriz de la Iglesia, Duncan G. Be...
SDM
2008
SIAM
133views Data Mining» more  SDM 2008»
13 years 11 months ago
Semantic Smoothing for Bayesian Text Classification with Small Training Data
Bayesian text classifiers face a common issue which is referred to as data sparsity problem, especially when the size of training data is very small. The frequently used Laplacian...
Xiaohua Zhou, Xiaodan Zhang, Xiaohua Hu