Product Question Answering in E-Commerce: A Survey

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