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Automatic Construction of Biomedical Abbreviations Dictionary from Text

机译:从文本自动构建生物医学缩写词典

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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.
机译:生物医学缩写的大小和增长率正在迅速提高,从文本自动构建生物医学缩写字典有助于理解生物医学文献,并有助于更新现有的数据库,本体和词典。通过结合字符串匹配算法和搜索算法,提出了一种从文本自动构建生物医学缩写词典的新方法。字符串匹配算法提取缩写及其长格式。搜索算法校正由字符串匹配算法产生的假长格式。搜索算法基于这样的思想,即读者经常查找相关文章以判断缩写的长格式正确与否。我们的实验表明,该算法具有较高的精度(97.5%)和召回率(82.2%)。并且由于不需要标记语料库,因此该方法具有很高的效率。

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