Improving Generalization with Active Learning
Machine Learning - Special issue on structured connectionist systems
Making large-scale support vector machine learning practical
Advances in kernel methods
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Less is More: Active Learning with Support Vector Machines
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Query Learning with Large Margin Classifiers
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Segmentation Using Eigenvectors: A Unifying View
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Support vector machine active learning with applications to text classification
The Journal of Machine Learning Research
On clusterings: Good, bad and spectral
Journal of the ACM (JACM)
Kernel k-means: spectral clustering and normalized cuts
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Thumbs up or thumbs down?: semantic orientation applied to unsupervised classification of reviews
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
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 sentimental education: sentiment analysis using subjectivity summarization based on minimum cuts
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Active learning with confidence
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Employing personal/impersonal views in supervised and semi-supervised sentiment classification
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Sentiment classification and polarity shifting
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
Active deep networks for semi-supervised sentiment classification
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Which clustering do you want? inducing your ideal clustering with minimal feedback
Journal of Artificial Intelligence Research
An affect-enriched dialogue act classification model for task-oriented dialogue
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Aspect ranking: identifying important product aspects from online consumer reviews
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Collaborative data cleaning for sentiment classification with noisy training corpus
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Sentiment classification via l2-norm deep belief network
Proceedings of the 20th ACM international conference on Information and knowledge management
Bilingual co-training for sentiment classification of chinese product reviews
Computational Linguistics
A cross-corpus study of unsupervised subjectivity identification based on calibrated EM
WASSA '11 Proceedings of the 2nd Workshop on Computational Approaches to Subjectivity and Sentiment Analysis
Learning opinions in user-generated web content
Natural Language Engineering
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Structural opinion mining for graph-based sentiment representation
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Using key sentence to improve sentiment classification
AIRS'11 Proceedings of the 7th Asia conference on Information Retrieval Technology
Semi-supervised learning for imbalanced sentiment classification
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Dual word and document seed selection for semi-supervised sentiment classification
Proceedings of the 21st ACM international conference on Information and knowledge management
Sample cutting method for imbalanced text sentiment classification based on BRC
Knowledge-Based Systems
Assembling the optimal sentiment classifiers
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
Ensemble learning for sentiment classification
CLSW'12 Proceedings of the 13th Chinese conference on Chinese Lexical Semantics
Bootstrapping polarity classifiers with rule-based classification
Language Resources and Evaluation
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Supervised polarity classification systems are typically domain-specific. Building these systems involves the expensive process of annotating a large amount of data for each domain. A potential solution to this corpus annotation bottleneck is to build unsupervised polarity classification systems. However, unsupervised learning of polarity is difficult, owing in part to the prevalence of sentimentally ambiguous reviews, where reviewers discuss both the positive and negative aspects of a product. To address this problem, we propose a semi-supervised approach to sentiment classification where we first mine the unambiguous reviews using spectral techniques and then exploit them to classify the ambiguous reviews via a novel combination of active learning, transductive learning, and ensemble learning.