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A transition-based joint model for disease named entity recognition and normalization

机译:一种基于转换的疾病联合模型,命名实体识别和归一化

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Motivation: Disease named entities play a central role in many areas of biomedical research, and automatic recognition and normalization of such entities have received increasing attention in biomedical research communities. Existing methods typically used pipeline models with two independent phases: (i) a disease named entity recognition (DER) system is used to find the boundaries of mentions in text and (ii) a disease named entity normalization (DEN) system is used to connect the mentions recognized to concepts in a controlled vocabulary. The main problems of such models are: (i) there is error propagation from DER to DEN and (ii) DEN is useful for DER, but pipeline models cannot utilize this.
机译:动机:命名实体的疾病在许多生物医学研究领域发挥着核心作用,自动识别和这些实体的正常化在生物医学研究社区中受到了不断的关注。 现有方法通常使用具有两个独立阶段的管道模型:(i)命名实体识别(der)系统的疾病用于查找文本中提到的边界和(ii)命名实体归一化(DEN)系统的疾病进行连接 提到认识到受控词汇中的概念。 此类模型的主要问题是:(i)从DER到DEN和(II)DEN的错误传播对DER非常有用,但流水线模型无法利用此。

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