WordNet: a lexical database for English
Communications of the ACM
Predicting the semantic orientation of adjectives
ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Mining and summarizing customer reviews
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
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
Accurate unlexicalized parsing
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Verbnet: a broad-coverage, comprehensive verb lexicon
Verbnet: a broad-coverage, comprehensive verb lexicon
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
Ontology-supported polarity mining
Journal of the American Society for Information Science and Technology
A holistic lexicon-based approach to opinion mining
WSDM '08 Proceedings of the 2008 International Conference on Web Search and Data Mining
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
BioNLP '06 Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis
Just how mad are you? finding strong and weak opinion clauses
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
The WEKA data mining software: an update
ACM SIGKDD Explorations Newsletter
Efficient Extraction of Protein-Protein Interactions from Full-Text Articles
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Fine-grained opinion mining by integrating multiple review sources
Journal of the American Society for Information Science and Technology
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The explosive growth of published articles in biomedical science field has led more research to focus on biomedical relationship extraction. However, there is relatively little investigation conducted on polarity analysis of these relationships, such as food (or nutrition) and disease relationships. 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 characteristics and challenges of relation polarity analysis, and then propose an integrated approach, which utilizes background knowledge in terms of relation word and polarity class association, and refines this association by using any available domain specific training data. In addition, we propose several novel learning features and a computational approach to construct background knowledge base. Empirical results on real world datasets show that the proposed method is effective.