Feature-rich part-of-speech tagging with a cyclic dependency network
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
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
Opinion Mining and Sentiment Analysis
Foundations and Trends in Information Retrieval
Sentiment analysis of blogs by combining lexical knowledge with text classification
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Fine-grained opinion mining by integrating multiple review sources
Journal of the American Society for Information Science and Technology
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In this paper, we investigate how to automatically identify the polarity of relationships between food and disease in biomedical text. In particular, we first analyze the characteristic and challenging of relation polarity analysis, and then propose a general approach, which utilizes background knowledge in terms of word-class association, and refines this information by using domain-specific training data. In addition, we propose several novel learning features. Experimental results on real world datasets show that the proposed approach is effective.