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Biomedical text disambiguation using UMLS

机译:使用UMLS进行生物医学文本消歧

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摘要

Interest in extracting information from biomedical documents has increased significantly in recent years but has always been challenged by the ambiguity of natural language. An important source of ambiguity is the usage of polysemous words: words with multiple meanings. Word sense disambiguation algorithms attempt to solve this problem by finding the correct meaning of a polysemous word in a given context, but very few algorithms were designed to disambiguate biomedical text. In this study we propose a word sense disambiguation algorithm focused on biomedical text. The proposed algorithm does not need to be trained and uses a relatively small knowledge base.
机译:近年来,从生物医学文献中提取信息的兴趣显着增加,但一直受到自然语言含混不清的挑战。模糊性的重要来源是多义词的使用:多义词。词义消歧算法试图通过在给定的上下文中找到多义词的正确含义来解决此问题,但是设计用于消除生物医学文本歧义的算法很少。在这项研究中,我们提出了一种针对生物医学文本的词义消歧算法。所提出的算法不需要训练,并且使用相对较小的知识库。

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