Automatic Construction of Biomedical Abbreviations Dictionary from Text

摘要：

The size and growth rate of biomedical abbreviation are increasing very fast, automatic construction of biomedical abbreviations dictionary from text helps to understand biomedical literature, and to update existing databases, ontologies, and dictionaries. This paper proposes a new method for automatic construction of biomedical abbreviations dictionary from text by combining string matching algorithm and searching algorithm. The string matching algorithm extracts abbreviations and their longforms. The searching algorithm corrects the false longforms produced by the string matching algorithm. The searching algorithm is based on the idea that readers often lookup relative articles to judge the longform of an abbreviation is correct or not. Our experiments show that the algorithm has high precision (97.5％) and recall (82.2％). And because tagged corpus is not necessary, the method has high efficiency.

关键词： Text mining biomedical abbreviations

作者: Changqin QUAN Fuji REN Tingting HE Po HU

作者单位: Dept.of Computer Science,Huazhong Normal University,Wuhan,China Dept.of Info.Science & Intelligent S Dept.of Info.Science & Intelligent Systems Faculty of Engineering,The University of Tokushima,Tokush Dept.of Computer Science,Huazhong Normal University,Wuhan,China

会议类型: 国际会议

会议名称: The 2008 IEEE International Conference on Natural Language Processing and Knowledge Engineering(IEEE NLP-KE 2008)(2008IEEE自然语言处理与知识工程国际会议)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-19（万方平台首次上网日期，不代表论文的发表时间）