Expert-Guided Contrastive Opinion Summarization for Controversial Issues
Expert-Guided Contrastive Opinion Summarization for Controversial Issues
复制标题
有争议问题的专家指导对比意见总结
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
Catherine Blake
中科院分区：
文献类型：
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作者：
Jinlong Guo;Yujie Lu;Tatsunori Mori;Catherine Blake
本文提出了一种新的模型，特别是有争议的问题的对比意见摘要（COS）的任务。传统的COS方法主要依赖于句子相似性度量，对于复杂的有争议的问题是不够的。因此，我们提出了一个专家指导的对比意见摘要（ECOS）模型。与以前的方法相比，我们的模型可以（1）整合专家意见与来自社交媒体的普通意见，（2）在专家先验意见的指导下更好地对齐对比论点。我们创建了一个新的数据集，一个复杂的社会问题与“足够”的争议和实验结果表明，该模型是有效的（1）产生更好的论点总结理解一个有争议的问题和（2）生成对比句子对。
This paper presents a new model for the task of contrastive opinion summarization (COS) particularly for controversial issues. Traditional COS methods, which mainly rely on sentence similarity measures are not sufficient for a complex controversial issue. We therefore propose an Expert-Guided Contrastive Opinion Summarization (ECOS) model. Compared to previous methods, our model can (1) integrate expert opinions with ordinary opinions from social media and (2) better align the contrastive arguments under the guidance of expert prior opinion. We create a new data set about a complex social issue with "sufficient" controversy and experimental results on this data show that the proposed model are effective for (1) producing better arguments summary in understanding a controversial issue and (2) generating contrastive sentence pairs.