Selecting typical instances in instance-based learning
ML92 Proceedings of the ninth international workshop on Machine learning
Use of the zero norm with linear models and kernel methods
The Journal of Machine Learning Research
Minimum spanning trees in hierarchical multiclass support vector machines generation
IEA/AIE'2005 Proceedings of the 18th international conference on Innovations in Applied Artificial Intelligence
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
EMNLP '03 Proceedings of the 2003 conference on Empirical methods in natural language processing
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
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Recognizing contextual polarity in phrase-level sentiment analysis
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Hierarchical document classification using automatically generated hierarchy
Journal of Intelligent Information Systems
Sentiment Detection Using Lexically-Based Classifiers
TSD '08 Proceedings of the 11th international conference on Text, Speech and Dialogue
TextGraphs-1 Proceedings of the First Workshop on Graph Based Methods for Natural Language Processing
ALT'09 Proceedings of the 20th international conference on Algorithmic learning theory
A comparison of methods for multiclass support vector machines
IEEE Transactions on Neural Networks
Authorship attribution with latent Dirichlet allocation
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
Review rating prediction based on the content and weighting strong social relation of reviewers
Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing
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This paper considers the problem of document-level multi-way sentiment detection, proposing a hierarchical classifier algorithm that accounts for the inter-class similarity of tagged sentiment-bearing texts. This type of classifier also provides a natural mechanism for reducing the feature space of the problem. Our results show that this approach improves on state-of-the-art predictive performance for movie reviews with three-star and four-star ratings, while simultaneously reducing training times and memory requirements.