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）旨在自动为电子商务平台中的客户问题提供即时响应，近年来受到越来越多的关注。与典型的问答问题相比，PQA展现出独特的挑战，例如电子商务平台中用户生成内容的主观性和可靠性。因此，研究者提出了多种问题设定和新颖方法来捕捉这些特殊特性。本文旨在系统性地回顾PQA领域现有的研究工作。具体而言，我们根据提供答案的形式将PQA研究分为四类问题设定。我们分析了每种设定的优缺点，并介绍了现有数据集和评估协议。我们进一步总结了PQA区别于一般问答应用的最显著挑战，并讨论了相应的解决方案。最后，本文通过展望几个未来方向进行总结。