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http://dx.doi.org/10.5626/KTCP.2017.23.3.194

Extraction of Protein-Protein Interactions based on Convolutional Neural Network (CNN)  

Choi, Sung-Pil (Kyonggi Univ.)
Publication Information
KIISE Transactions on Computing Practices / v.23, no.3, 2017 , pp. 194-198 More about this Journal
Abstract
In this paper, we propose a revised Deep Convolutional Neural Network (DCNN) model to extract Protein-Protein Interaction (PPIs) from the scientific literature. The proposed method has the merit of improving performance by applying various global features in addition to the simple lexical features used in conventional relation extraction approaches. In the experiments using AIMed, which is the most famous collection used for PPI extraction, the proposed model shows state-of-the art scores (78.0 F-score) revealing the best performance so far in this domain. Also, the paper shows that, without conducting feature engineering using complicated language processing, convolutional neural networks with embedding can achieve superior PPIE performance.
Keywords
protein-protein interaction extraction; convolutional networks; information extraction; deep learning; machine learning;
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