Camouflaged Chinese Spam Content Detection with Semi-supervised Generative Active Learning

ACL, pp. 3080-3085, 2020.

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We propose a supervIsed GeNerative Active Learning model for Chinese text spam detection

Abstract:

We propose a Semi-supervIsed GeNerative Active Learning (SIGNAL) model to address the imbalance, efficiency, and text camouflage problems of Chinese text spam detection task. A “self-diversity” criterion is proposed for measuring the “worthiness” of a candidate for annotation. A semi-supervised variational autoencoder with masked attentio...More
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