计算机工程2011，Vol.37Issue(10)：184-186,3.DOI:10.3969/j.issn.1000-3428.2011.10.063
基于多核学习的医学文献蛋白质关系抽取
Protein-protein Interaction Extraction from Medical Literature Based on Multiple Kernels Learning
摘要
Abstract
Automatic extracting protein-protein interaction information from biomedical literature can help to build protein relation network and design new drugs.This paper presents a multiple kernels learning based approach to automatically extract protein-protein interactions from biomedical literature.The approach combines feature-based kernel, tree kernel and graph kernel.In particular, it extends shortest path-enclosed tree and dependency path tree to capture richer contextual information.Experimental evaluations show that the method can achieve state-of-the-art performance with respect to comparable evaluations, with 63.9％ F-score and 87.83％ AUC on the AImed corpus.关键词
文本挖掘/信息抽取/蛋白质关系抽取/核方法/多核学习Key words
text mining/ information extraction/ protein-protein interaction extraction/ kernel method/ multiple kernels learning分类
信息技术与安全科学引用本文复制引用
唐楠,杨志豪,林鸿飞,李彦鹏..基于多核学习的医学文献蛋白质关系抽取[J].计算机工程,2011,37(10):184-186,3.基金项目
国家自然科学基金资助项目(60373095,60673039) （60373095,60673039）
国家"863"计划基金资助项目(2006AA01Z151) （2006AA01Z151）
