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BMCBI
2010

Learning an enriched representation from unlabeled data for protein-protein interaction extraction

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Learning an enriched representation from unlabeled data for protein-protein interaction extraction
Background: Extracting protein-protein interactions from biomedical literature is an important task in biomedical text mining. Supervised machine learning methods have been used with great success in this task but they tend to suffer from data sparseness because of their restriction to obtain knowledge from limited amount of labelled data. In this work, we study the use of unlabeled biomedical texts to enhance the performance of supervised learning for this task. We use feature coupling generalization (FCG)
Yanpeng Li, Xiaohua Hu, Hongfei Lin, Zhihao Yang
Added 08 Dec 2010
Updated 08 Dec 2010
Type Journal
Year 2010
Where BMCBI
Authors Yanpeng Li, Xiaohua Hu, Hongfei Lin, Zhihao Yang
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