Training products of experts by minimizing contrastive divergence
Neural Computation
Support vector machine active learning with applications to text classification
The Journal of Machine Learning Research
Thumbs up?: sentiment classification using machine learning techniques
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
A fast learning algorithm for deep belief nets
Neural Computation
A sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Self-taught learning: transfer learning from unlabeled data
Proceedings of the 24th international conference on Machine learning
Semi-supervised learning of compact document representations with deep networks
Proceedings of the 25th international conference on Machine learning
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Document-Word Co-regularization for Semi-supervised Sentiment Analysis
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Multi-domain sentiment classification
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Automatic seed word selection for unsupervised sentiment classification of Chinese text
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Co-training for cross-lingual sentiment classification
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 1 - Volume 1
Mine the easy, classify the hard: a semi-supervised approach to automatic sentiment classification
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Learning Deep Architectures for AI
Learning Deep Architectures for AI
Sentiment analysis using a novel human computation game
Proceedings of the 3rd Workshop on the People's Web Meets NLP: Collaboratively Constructed Semantic Resources and their Applications to NLP
Pattern classification and clustering: A review of partially supervised learning approaches
Pattern Recognition Letters
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This paper presents a novel semi-supervised learning algorithm called Active Deep Networks (ADN), to address the semi-supervised sentiment classification 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 supervised learning with an exponential loss function. Second, we apply active learning in the semi-supervised learning framework to identify reviews that should be labeled as training data. Then ADN architecture is trained by the selected labeled data and all unlabeled data. Experiments on five sentiment classification datasets show that ADN outperforms the semi-supervised learning algorithm and deep learning techniques applied for sentiment classification.