Paper: Active Deep Networks for Semi-Supervised Sentiment Classification

ACL ID C10-2173
Title Active Deep Networks for Semi-Supervised Sentiment Classification
Venue International Conference on Computational Linguistics
Session Poster Session
Year 2010
Authors

This paper presents a novel semi- supervised learning algorithm called Ac- tive Deep Networks (ADN), to address the semi-supervised sentiment classifica- tion problem with active learning. First, we propose the semi-supervised learning method of ADN. ADN is constructed by Restricted Boltzmann Machines (RBM) with unsupervised learning using labeled data and abundant of unlabeled data. Then the constructed structure is fine- tuned by gradient-descent based super- vised learning with an exponential loss function. Second, we apply active learn- ing in the semi-supervised learning framework to identify reviews that should be labeled as training data. Then ADN architecture is trained by the se- lected labeled data and all unlabeled data. Experiments on five sentiment classifica- tio...