计算机科学 ›› 2017, Vol. 44 ›› Issue (10): 249-253.doi: 10.11896/j.issn.1002-137X.2017.10.045
刘凯,符海东,邹玉薇,顾进广
LIU Kai, FU Hai-dong, ZOU Yu-wei and GU Jin-guang
摘要: 随着医疗领域受到越来越多的关注,自然语言处理的理论和应用逐渐拓展到该领域,其中信息抽取技术在该领域的应用成为研究热点。针对信息抽取技术在医疗领域实体关系抽取中的应用,提出一种基于卷积神经网络的弱监督关系抽取方法。该方法通过添加人工规则使训练语料带有实体关系标签,然后将该弱关系训练语料转换为向量特征矩阵,并输入到卷积神经网络进行分类模型训练,最终实现实体关系抽取。实验结果表明,该方法比常规机器学习方法更加准确高效。
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