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

作　　者：CHEN Bo Lü Chen WEI Xiaomei JI 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》2015年第2期141-145,共5页武汉大学学报（自然科学英文版）

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 postpositire 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.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 postpositire 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：biomedical text mining semantic annotation recursive directed graph postpositive attribute 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论] TB383[自动化与计算机技术—计算机科学与技术]