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Biomedical Text Disambiguation using UMLS

机译:生物医学文本使用UML歧义

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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,对生物医学文件中的信息提取信息的兴趣显着增加,但始终受到自然语言的模糊性挑战。一个重要的歧义来源是使用多种词语的使用:具有多种含义的单词。字感歧义算法尝试通过在给定的上下文中查找多态词的正确含义来解决这个问题,但很少有算法旨在消除生物医学文本。在这项研究中,我们提出了一种重点在生物医学文本上的词感歧义算法。所提出的算法不需要培训并使用相对小的知识库。

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