ALICE: An algorithm to extract abbreviations from MEDLINE
ALICE: An algorithm to extract abbreviations from MEDLINE
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DOI：
10.1197/jamia.m1757
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发表时间：
2005-09-01
影响因子：
6.4
通讯作者：
Takagi, TI
中科院分区：
文献类型：
--
作者：
Ao, H;Takagi, TI
目的：为了帮助生物医学研究人员识别生物医学文献中动态引入的缩写，如基因和蛋白质名称，我们构建了一个支持系统ALICE（使用基于语料库的提取后的缩写）。ALICE的目标是从一篇目标论文中动态地抽取所有类型的缩略语及其扩展。方法：ALICE利用启发式模式匹配规则从文献中抽取缩略语及其扩展。该系统包括三个阶段，并可能识别有效的320缩写扩展模式的组合rules.Results：它达到了95%的召回率和97%的精度随机选择的标题和摘要从MEDLINE database.Conclusion：ALICE提取缩写及其扩展有效的文献。巧妙编译的缩略语使其能够以高召回率提取缩写，而不会显着降低精度。ALICE不仅可以通过构建缩略语数据库或词典来识别论文中未定义的缩略语，而且可以使生物医学文献检索更加准确。
Objective: To help biomedical researchers recognize dynamically introduced abbreviations in biomedical literature, such as gene and protein names, we have constructed a support system called ALICE (Abbreviation Llfter using Corpus-based Extraction). ALICE aims to extract all types of abbreviations with their expansions from a target paper on the fly.Methods: ALICE extracts an abbreviation and its expansion from the literature by using heuristic pattern-matching rules. This system consists of three phases and potentially identifies valid 320 abbreviation-expansion patterns as combinations of the rules.Results: It achieved 95% recall and 97% precision on randomly selected titles and abstracts from the MEDLINE database.Conclusion: ALICE extracted abbreviations and their expansions from the literature efficiently. The subtly compiled heuristics enabled it to extract abbreviations with high recall without significantly reducing precision. ALICE does not only facilitate recognition of an undefined abbreviation in a paper by constructing an abbreviation database or dictionary, but also makes biomedical literature retrieval more accurate.