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» Sampling the Web as Training Data for Text Classification
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NAACL
2010
15 years 29 days ago
Subword Variation in Text Message Classification
For millions of people in less resourced regions of the world, text messages (SMS) provide the only regular contact with their doctor. Classifying messages by medical labels suppo...
Robert Munro, Christopher D. Manning
KDD
2008
ACM
195views Data Mining» more  KDD 2008»
16 years 3 months ago
Learning from multi-topic web documents for contextual advertisement
Contextual advertising on web pages has become very popular recently and it poses its own set of unique text mining challenges. Often advertisers wish to either target (or avoid) ...
Yi Zhang, Arun C. Surendran, John C. Platt, Mukund...
MCS
2007
Springer
15 years 9 months ago
Random Feature Subset Selection for Ensemble Based Classification of Data with Missing Features
Abstract. We report on our recent progress in developing an ensemble of classifiers based algorithm for addressing the missing feature problem. Inspired in part by the random subsp...
Joseph DePasquale, Robi Polikar
BIBE
2010
IEEE
143views Bioinformatics» more  BIBE 2010»
15 years 4 months ago
The Effect of Sequence Error and Partial Training Data on BLAST Accuracy
- Metagenomics is the study of environmental samples. Because few tools exist for metagenomic analysis, a natural step has been to utilize the popular homology tool, BLAST, to sear...
Steven D. Essinger, Gail L. Rosen
AUSDM
2006
Springer
144views Data Mining» more  AUSDM 2006»
15 years 6 months ago
A Characterization of Wordnet Features in Boolean Models For Text Classification
Supervised text classification is the task of automatically assigning a category label to a previously unlabeled text document. We start with a collection of pre-labeled examples ...
Trevor N. Mansuy, Robert J. Hilderman