Exploiting the performance of dictionary-based bio-entity name recognition in biomedical literature

被引:47
|
作者
Yang, Zhihao [1 ]
Lin, Hongfei [1 ]
Li, Yanpeng [1 ]
机构
[1] Dalian Univ Technol, Dept Comp Sci & Engn, Dalian 116023, Peoples R China
基金
中国国家自然科学基金;
关键词
text mining; entity recognition; edit distance; conditional random fields;
D O I
10.1016/j.compbiolchem.2008.03.008
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Bio-entity name recognition is the key step for information extraction from biomedical literature. This paper presents a dictionary-based bio-entity name recognition approach. The approach expands the bio-entity name dictionary via the Abbreviation Definitions identifying algorithm, improves the recall rate through the improved edit distance algorithm and adopts some post-processing methods including Pre-keyword and Post-keyword expansion, Part of Speech expansion, merge of adjacent bio-entity names and the exploitation of the contextual cues to further improve the performance. Experiment results show that with this approach even an internal dictionary-based system could achieve a fairly good performance. (C) 2008 Elsevier Ltd. All rights reserved.
引用
收藏
页码:287 / 291
页数:5
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