English

Product Question Answering in E-Commerce: A Survey

Computation and Language 2023-05-04 v2 Information Retrieval

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 solutions. Finally, we conclude this paper by providing the prospect on several future directions.

Keywords

Cite

@article{arxiv.2302.08092,
  title  = {Product Question Answering in E-Commerce: A Survey},
  author = {Yang Deng and Wenxuan Zhang and Qian Yu and Wai Lam},
  journal= {arXiv preprint arXiv:2302.08092},
  year   = {2023}
}

Comments

Accepted by ACL 2023 main conference

R2 v1 2026-06-28T08:41:29.152Z