计算机科学 ›› 2022, Vol. 49 ›› Issue (11): 206-211.doi: 10.11896/jsjkx.210900120
程华龄, 陈艳平, 杨卫哲, 秦永彬, 黄瑞章
CHENG Hua-ling, CHEN Yan-ping, YANG Wei-zhe, QIN Yong-bin, HUANG Rui-zhang
摘要： 关系抽取旨在从句子中识别出实体对之间的关系类型。在关系抽取领域,目前主流的方法都使用了深度学习方法,但大部分方法在输入层没有对词向量进行深层次的讨论。针对这一不足,提出了一种基于多维语义映射的关系抽取方法,该方法的核心思想是将矩阵降维方法应用于神经网络模型输入层。通过将表示文本的词向量进行多维度的降维分解,使分解后的词向量能映射表示同一语句在不同维度上的语义信息。实验结果表明,在Chinese Literature Text和SemEval-2010 Task8数据集上F1值分别达到了75.3%和88.9%,验证了所提方法的有效性。
中图分类号:
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