计算机科学 ›› 2023, Vol. 50 ›› Issue (11A): 220900266-6.doi: 10.11896/jsjkx.220900266
林正超, 李弼程
LIN Zhengchao, LI Bicheng
摘要： 方面级情感分析是目前自然语言处理领域的一个重要研究方向,其目的是预测句子当中不同方面的情感极性。现有的方面级情感分析,通常忽略了情感极性与局部语境之间的关系,且在部分使用多头注意力机制的研究中,每个注意力头数的运算是相互独立的。为此,提出了一种基于局部上下文焦点机制和交谈注意力的方面级情感分析模型。首先,通过BERT预训练模型分别捕获局部上下文和全局上下文的初步特征。然后,在特征提取层,利用局部上下文焦点机制,通过上下文特征动态掩码层结合交谈注意力机制来进一步提取局部上下文特征;利用交谈注意力机制进一步提取全局上下文特征。最后,将局部和全局信息进行融合,输入非线性层获取情感分析结果。在3个公开数据集上进行了对比实验,实验结果表明,与现有的多个基线模型相比,所提模型的MF1值和准确率均有提升。
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