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IJCAI
2003
13 years 7 months ago
Integrating Background Knowledge Into Text Classification
We present a description of three different algorithms that use background knowledge to improve text classifiers. One uses the background knowledge as an index into the set of tra...
Sarah Zelikovitz, Haym Hirsh
ML
2000
ACM
124views Machine Learning» more  ML 2000»
13 years 5 months ago
Text Classification from Labeled and Unlabeled Documents using EM
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
FLAIRS
2008
13 years 8 months ago
Building Useful Models from Imbalanced Data with Sampling and Boosting
Building useful classification models can be a challenging endeavor, especially when training data is imbalanced. Class imbalance presents a problem when traditional classificatio...
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van H...
CVPR
2003
IEEE
14 years 7 months ago
Learning Bayesian Network Classifiers for Facial Expression Recognition using both Labeled and Unlabeled Data
Understanding human emotions is one of the necessary skills for the computer to interact intelligently with human users. The most expressive way humans display emotions is through...
Ira Cohen, Nicu Sebe, Fabio Gagliardi Cozman, Marc...
CLEF
2010
Springer
13 years 6 months ago
ZOT! to Wikipedia Vandalism - Lab Report for PAN at CLEF 2010
Abstract This vandalism detector uses features primarily derived from a wordpreserving differencing of the text for each Wikipedia article from before and after the edit, along wit...
James White, Rebecca Maessen