Product question answering (PQA), aiming to automatically provide instant responses to customer's questions in E-Commerce platforms, has drawn increasing attention in recent years. Compared with typical QA problems, PQA exhibits unique challenges such as the subjectivity and reliability of user-generated contents in E-commerce platforms. Therefore, various problem settings and novel methods have been proposed to capture these special characteristics. In this paper, we aim to systematically review existing research efforts on PQA. Specifically, we categorize PQA studies into four problem settings in terms of the form of provided answers. We analyze the pros and cons, as well as present existing datasets and evaluation protocols for each setting. We further summarize the most significant challenges that characterize PQA from general QA applications and discuss their corresponding solutions. Finally, we conclude this paper by providing the prospect on several future directions.

翻译：产品问答（PQA）旨在自动为电商平台上的客户问题提供即时回答，近年来受到越来越多的关注。与典型问答任务相比，PQA面临独特挑战，例如电商平台用户生成内容的主观性与可靠性问题。因此，研究者提出了一系列问题设置与创新方法来捕捉这些特殊特征。本文旨在系统回顾PQA领域的现有研究成果。具体而言，我们根据答案形式将PQA研究划分为四类问题设置，分析各类设置的优缺点，并介绍现有数据集与评估协议。我们进一步总结了PQA区别于通用问答应用的核心挑战，并讨论其相应解决方案。最后，本文展望了未来若干研究方向作为结论。