Semantic Relation Annotation for Biomedical Text Mining Based on Recursive Directed Graph

查看全文 作　　者：CHEN [1,2]Bo;Lü [1]Chen;WEI [1]Xiaomei;JI [1]Donghong

机构地区：[1]School of Computer, Wuhan University;[2]Department of Chinese Language and Literature, Hubei University of Art and Science

出　　处：《Wuhan University Journal of Natural Sciences》索引2015年第20卷第2期,共5页

基　　金：Supported by the National Natural Science Foundation of China(61202193,61202304);the Major Projects of Chinese National Social Science Foundation(11&ZD189);the Chinese Postdoctoral Science Foundation(2013M540593,2014T70722) 摘　　要：In this paper we propose a novel model 'recursive directed graph' based on feature structure, and apply it to represent the semantic relations of postpositive attributive structures in biomedical texts. The usages of postpositive attributive are complex and variable, especially three categories: present participle phrase, past participle phrase, and preposition phrase as postpositive attributive, which always bring the difficulties of automatic parsing. We summarize these categories and annotate the semantic information. Compared with dependency structure, feature structure, being recursive directed graph, enhances semantic information extraction in biomedical field. The annotation results show that recursive directed graph is more suitable to extract complex semantic relations for biomedical text mining. 关键词：生物医学语义关系文本挖掘功能结构递推标注信息提取自动解析

相关文献

参考文献（15）
引证文献（2）
耦合文献（8）

参考文献(15)

引证文献(2)

耦合文献(8)

互联网出版许可证新出网证(渝)字10号全国400电话 - 免长途话费

Semantic Relation Annotation for Biomedical Text Mining Based on Recursive Directed Graph

参考文献(15)

引证文献(2)

耦合文献(8)

用户提示