计算机科学 ›› 2022, Vol. 49 ›› Issue (5): 221-226.doi: 10.11896/jsjkx.210400135
李子仪, 周夏冰, 王中卿, 张民
LI Zi-yi, ZHOU Xia-bing, WANG Zhong-qing, ZHANG Min
摘要: 立场检测的主要目的是挖掘用户对话题或事件等的立场态度。与其他文本分类任务不同,立场的表达更隐晦,立场的态度对用户更加敏感。目前已有的立场检测方法主要是对话题内容自身信息进行建模,该类方法忽略了话题内容的用户背景信息,但用户及其喜好信息极大地影响着对文本信息的精准挖掘,通过关联用户信息能够获得潜在的信息特征。因此,提出了基于用户关联的立场检测模型(USDM),通过构建用户之间的图网络来建立用户关联结构,利用卷积操作挖掘相同用户下相似的文本立场信息,从全局的角度构建立场检测模型。同时,加入注意力机制以增强文本用户感知表示。在公开数据集H&N14上的实验结果表明,相比其他模型,所提模型获得了较好的性能。同时,消融实验表明,考虑用户关联以及注意力机制对检测准确率的提升具有重要作用。
中图分类号:
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