论文标题
基于DPP的社区质量保证的多样化和非冗余答案设置提取
Diverse and Non-redundant Answer Set Extraction on Community QA based on DPPs
论文作者
论文摘要
在基于社区的问答（CQA）平台中，用户需要花费时间从许多答案中获取有用的信息。尽管一个解决方案是一种答案排名方法，但用户仍然需要仔细阅读排名最高的答案。本文提出了一项新的任务，即选择一个多样的和非冗余的答案集，而不是对答案进行排名。我们的方法基于确定点过程（DPP），它通过使用BERT来计算答案之间的重要性和相似性。我们构建了一个针对日本CQA站点的数据集，该数据集的实验表明，所提出的方法的表现优于几种基线方法。
In community-based question answering (CQA) platforms, it takes time for a user to get useful information from among many answers. Although one solution is an answer ranking method, the user still needs to read through the top-ranked answers carefully. This paper proposes a new task of selecting a diverse and non-redundant answer set rather than ranking the answers. Our method is based on determinantal point processes (DPPs), and it calculates the answer importance and similarity between answers by using BERT. We built a dataset focusing on a Japanese CQA site, and the experiments on this dataset demonstrated that the proposed method outperformed several baseline methods.
