Mining Terminological Knowledge in Large Biomedical Corpora
Mining Terminological Knowledge in Large Biomedical Corpora
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DOI：
10.1142/9789812776303_0039
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发表时间：
2002-12
影响因子：
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通讯作者：
Hongfang Liu;C. Friedman
中科院分区：
文献类型：
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作者：
Hongfang Liu;C. Friedman
生物医学领域的术语知识对于自然语言处理（NLP）和信息检索（IR）应用非常重要，并且已经存在许多术语知识源，例如LocusLink，GeneBank和UMLS。然而，由于该领域的大量研究活动，新的术语和符号不断被创造出来，其中许多在文献中发表，但在任何其他资源中都不可用。因此，有效地挖掘文献中的新术语对于促进NLP和IR应用至关重要。缩略语广泛应用于生物医学领域，理解缩略语需要一个由缩略语及其相关含义组成的术语知识库。在以前的工作中，已经开发了几种方法自动构建的缩写知识库从括号表达式。然而，这些方法根据手动构建的模式或规则对缩写及其扩展进行配对。本文提出了一种不基于模式或规则，而是基于搭配使用的自动方法，从插入语中自动提取一组相关术语，包括与其扩展相关联的缩写以及其他类型的相关术语，如同义词或下义词等。我们的方法基于以下观察：与插入语相关联的术语i）通常是相关的，和ii）经常是搭配，因为它们往往比预期的更经常地同时出现。我们的方法被应用到收集MEDLINE摘要。方法和结果进行了评估，使用两个集合：伯曼的手工缩写列表和LocusLink集合。
Terminological knowledge of the biomedical domain is important for natural language processing (NLP) and information retrieval (IR) applications, and a number of terminological knowledge sources, such as LocusLink, GeneBank, and the UMLS, already exist. However, because of the tremendous amount of research activity in the field, new terms and symbols are continually being created, many of which are published in the literature, but are not available in any of the other resources. Therefore, effective mining of the literature for new terminology is critical for furthering NLP and IR applications. Abbreviations are widely used in the biomedical domain, and the understanding of abbreviations requires a terminological knowledge base that consists of abbreviations with their associated senses. In previous work, several methods have been developed for automatic construction of abbreviation knowledge bases from parenthetical expressions. However, these methods pair abbreviations and their expansions based on manually crafted patterns or rules. In this paper, we propose an automatic method, which is not based on patterns or rules but is based on the use of collocations, to extract a set of related terms from parenthetical expressions including abbreviations associated with their expansions and other types of related terms such as synonyms, or hyponyms etc. Our method is based on the observation that terms associated with parenthetical expressions i) are usually related, and ii) are often collocations because they tend to co-occur more often than expected by chance. Our method was applied to the collection of MEDLINE abstracts. The method and the results were evaluated using two collections: Berman's handcrafted abbreviation list and the LocusLink collection.