title: Drug-Drug Interaction Extraction via Convolutional Neural Networks.
abstract: Drug-drug interaction (DDI) extraction as a typical relation extraction task in natural language processing (NLP) has always attracted great attention. Most state-of-the-art DDI extraction systems are based on support vector machines (SVM) with a large number of manually defined features. Recently, convolutional neural networks (CNN), a robust machine learning method which almost does not need manually defined features, has exhibited great potential for many NLP tasks. It is worth employing CNN for DDI extraction, which has never been investigated. We proposed a CNN-based method for DDI extraction. Experiments conducted on the 2013 DDIExtraction challenge corpus demonstrate that CNN is a good choice for DDI extraction. The CNN-based DDI extraction method achieves an F-score of 69.75%, which outperforms the existing best performing method by 2.75%.
authors.affiliation: Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China.
authors.forename: Shengyu
authors.initials: S
authors.lastname: Liu
authors.affiliation: Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China.
authors.forename: Buzhou
authors.initials: B
authors.lastname: Tang
authors.affiliation: Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China.
authors.forename: Qingcai
authors.initials: Q
authors.lastname: Chen
authors.affiliation: Key Laboratory of Network Oriented Intelligent Computation, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen 518055, China.
authors.forename: Xiaolong
authors.initials: X
authors.lastname: Wang
mesh_terms: D000465:Algorithms; D057225:Data Mining / Q000379:methods; D004347:Drug Interactions; D006801:Humans; D000069550:Machine Learning; D015233:Models, Statistical; D009323:Natural Language Processing; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods; D012044:Regression Analysis; D012660:Semantics; D060388:Support Vector Machine