Exploiting Dependency Information for Feature-Based Protein-Protein Interaction Extraction

被引：0

作者：

Liu, Bing ^{[1
]}

Qian, Longhua ^{[1
]}

Zhou, Guodong ^{[1
]}

Zhu, Qiaoming ^{[1
]}

机构：

[1] Soochow Univ, Sch Comp Sci & Technol, Suzhou, Peoples R China

来源：

PROCEEDINGS OF THE 2011 INTERNATIONAL CONFERENCE ON INFORMATICS, CYBERNETICS, AND COMPUTER ENGINEERING (ICCE2011), VOL 2: INFORMATION SYSTEMS AND COMPUTER ENGINEERING | 2011年 / 111卷

关键词：

Protein-Protein Interaction; SVM; Dependency information;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper investigates the combination of diverse lexical, syntactic and semantic information in feature-based protein-protein interaction extraction using SVM. Our study illustrates that dependency information as well as base phrase chunking information is very effective for feature-based PPI extraction while the full parse feature have less effect on the overall performance. Experimental evaluation on the AIMed corpus shows that our system achieves a promising performance of 54.7 in F-measure, surpassing other state-of-the-art feature-based ones.

引用

页码：267 / 272

页数：6

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