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        <title>基于循环交互注意力网络的问答立场分析(A Recurrent Interactive Attention Network for Answer Stance Analysis)</title>
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    <name type="personal">
        <namePart type="given">Bin</namePart>
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    <name type="personal">
        <namePart type="given">Ruifeng</namePart>
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    <abstract>针对问答立场任务中,现有方法难以提取问答文本间的依赖关系问题,本文提出一种基于循环交互注意力(Recurrent Interactive Attention, RIA)网络的问答立场分析方法。该方法通过模仿人类阅读理解时的思维方式,基于交互注意力机制和循环迭代方法,有效地从问题和答案的相互联系中挖掘问答文本的立场信息。此外,该方法将问题进行陈述化表示,有效地解决疑问句表述下问题文本无法明确表达自身立场的问题。实验结果表明,本文方法取得了比现有模型方法更好的效果,同时证明该方法能有效拟合问答立场分析任务中的问答对依赖关系。</abstract>
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%0 Conference Proceedings
%T 基于循环交互注意力网络的问答立场分析(A Recurrent Interactive Attention Network for Answer Stance Analysis)
%A Luo, Wangda
%A Liu, Yuhan
%A Liang, Bin
%A Xu, Ruifeng
%S Proceedings of the 19th Chinese National Conference on Computational Linguistics
%D 2020
%8 oct
%I Chinese Information Processing Society of China
%C Haikou, China
%G Chinese
%F luo-etal-2020-ji
%X 针对问答立场任务中,现有方法难以提取问答文本间的依赖关系问题,本文提出一种基于循环交互注意力(Recurrent Interactive Attention, RIA)网络的问答立场分析方法。该方法通过模仿人类阅读理解时的思维方式,基于交互注意力机制和循环迭代方法,有效地从问题和答案的相互联系中挖掘问答文本的立场信息。此外,该方法将问题进行陈述化表示,有效地解决疑问句表述下问题文本无法明确表达自身立场的问题。实验结果表明,本文方法取得了比现有模型方法更好的效果,同时证明该方法能有效拟合问答立场分析任务中的问答对依赖关系。
%U https://aclanthology.org/2020.ccl-1.65
%P 698-706

Markdown (Informal)

[基于循环交互注意力网络的问答立场分析(A Recurrent Interactive Attention Network for Answer Stance Analysis)](https://aclanthology.org/2020.ccl-1.65) (Luo et al., CCL 2020)

• 基于循环交互注意力网络的问答立场分析(A Recurrent Interactive Attention Network for Answer Stance Analysis) (Luo et al., CCL 2020)

ACL

• Wangda Luo, Yuhan Liu, Bin Liang, and Ruifeng Xu. 2020. 基于循环交互注意力网络的问答立场分析(A Recurrent Interactive Attention Network for Answer Stance Analysis). In Proceedings of the 19th Chinese National Conference on Computational Linguistics, pages 698–706, Haikou, China. Chinese Information Processing Society of China.