Improving Text Classification Accuracy by Training Label Cleaning

@article{Esuli2013ImprovingTC,
  title={Improving Text Classification Accuracy by Training Label Cleaning},
  author={Andrea Esuli and Fabrizio Sebastiani},
  journal={ACM Trans. Inf. Syst.},
  year={2013},
  volume={31},
  pages={19:1-19:28}
}
In text classification (TC) and other tasks involving supervised learning, labelled data may be scarce or expensive to obtain. Semisupervised learning and active learning are two strategies whose aim is maximizing the effectiveness of the resulting classifiers for a given amount of training effort. Both strategies have been actively investigated for TC in recent years. Much less research has been devoted to a third such strategy, training label cleaning (TLC), which consists in devising ranking… CONTINUE READING
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Reuters-21578 text categorization test collection Distribution 1.0 README file (v 1.3)

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