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Identifying Unclear Questions in Community Question Answering Websites

机译:在社区问答网站中识别不清楚的问题

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Thousands of complex natural language questions are submitted to community question answering websites on a daily basis, rendering them as one of the most important information sources these days. However, oftentimes submitted questions are unclear and cannot be answered without further clarification questions by expert community members. This study is the first to investigate the complex task of classifying a question as clear or unclear, i.e., if it requires further clarification. We construct a novel dataset and propose a classification approach that is based on the notion of similar questions. This approach is compared to state-of-the-art text classification baselines. Our main finding is that the similar questions approach is a viable alternative that can be used as a stepping stone towards the development of supportive user interfaces for question formulation.
机译:每天有成千上万种复杂的自然语言问题提交到社区问答网站,使其成为当今最重要的信息来源之一。但是,通常提交的问题不清楚,如果没有专家社区成员的进一步澄清问题,就无法回答。这项研究是第一个研究将问题分类为清晰还是不清楚(即是否需要进一步澄清)的复杂任务。我们构建了一个新颖的数据集,并提出了一种基于类似问题概念的分类方法。将该方法与最新的文本分类基准进行了比较。我们的主要发现是,类似的问题方法是可行的替代方法,可以用作开发支持用户界面以制定问题的垫脚石。

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