Product Question Answering in E-Commerce: A Survey
Yang Deng, Wenxuan Zhang, Qian Yu, Wai Lam

TL;DR
This survey reviews the unique challenges, problem settings, datasets, and evaluation methods in product question answering for e-commerce, highlighting recent research efforts and future directions.
Contribution
It systematically categorizes PQA problem settings, analyzes existing methods and datasets, and discusses challenges and solutions specific to e-commerce PQA.
Findings
Categorized PQA into four answer formats
Analyzed datasets and evaluation protocols for each setting
Identified key challenges and proposed solutions in PQA
Abstract
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…
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Taxonomy
TopicsExpert finding and Q&A systems · Service-Oriented Architecture and Web Services · Sentiment Analysis and Opinion Mining
