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Relation Extraction from Traditional Chinese Medicine Journal Publication

机译:中医杂志出版物的关系提取

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This modern day, the amount of digital text documents is enormous and cover almost all fields and industry. Natural Language Processing (NLP) looks into systematically deriving information from text written in natural language. A task under NLP, Relation Extraction (ER) focus on identifying relations from natural text. It has found significant application on biomedical publications, where it has been used to identify protein-to-protein interaction and gene-to-disease relationships in biomedical publications. Such application is also effective on Traditional Chinese Medicine (TCM) publications. This research identifies two forms of relations in TCM publications: Effect Relation and Conditional Effect Relation. This research introduces and compares two extraction approaches, in which also address some of the more Chinese-specific NLP problems, such as word segmentation and flexible syntactic structure.
机译:这个现代化的一天,数字文本文件的数量是巨大的,几乎覆盖了所有的领域和行业。自然语言处理(NLP)正在系统地从自然语言中编写的文本中获取信息。 NLP下的任务,关系提取(ER)侧重于识别自然文本的关系。它发现了对生物医学出版物的重要应用,其中用于鉴定生物医学出版物中的蛋白质对蛋白质相互作用和基因对疾病关系。这种应用在中医(TCM)出版物上也有效。本研究确定了中医出版物中的两种关系:效应关系和条件效应关系。该研究介绍了两种提取方法,其中还解决了一些更多的中文特定NLP问题,例如文字分割和灵活的句法结构。

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