计算机科学 ›› 2026, Vol. 53 ›› Issue (3): 341-350.doi: 10.11896/jsjkx.250300039
郝渊斌1, 段利国1,2, 李爱萍1, 陈嘉昊1, 崔娟娟1, 常轩伟1
HAO Yuanbin1, DUAN Liguo1,2, LI Aiping1, CHEN Jiahao1, CUI Juanjuan1, CHANG Xuanwei1
摘要： 方面情感三元组抽取(ASTE)旨在同时提取出文本中的方面及其对应的观点和情感极性,是一项新兴且具有挑战性的方面级情感分析任务。现有方法中,基于多轮机器阅读理解的方法有效实现了情感三元组抽取,但仍存在一定的局限性:其一,多轮阅读理解中单一的文本特征难以适应特定子任务;其二,全局自注意力机制缺乏对语法层面更重要单词的关注,且其对不重要单词赋予更高的注意力权重。针对这些问题,提出一种特征增强式多轮机器阅读理解方法(EMT-MRC),在每轮机器阅读理解中设计双向注意力流构建文本与问题的交互关系,从而获得特定任务感知的文本表示。同时,将依存句法关系整合到Transformer编码器,通过依存距离约束模型注意力分布,加强模型对句子语法层面的关注。通过在两组基准数据集上的实验,证明了提出方法的有效性。
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