English

Generate-then-Retrieve: Intent-Aware FAQ Retrieval in Product Search

Computation and Language 2023-06-07 v1 Artificial Intelligence Information Retrieval

Abstract

Customers interacting with product search engines are increasingly formulating information-seeking queries. Frequently Asked Question (FAQ) retrieval aims to retrieve common question-answer pairs for a user query with question intent. Integrating FAQ retrieval in product search can not only empower users to make more informed purchase decisions, but also enhance user retention through efficient post-purchase support. Determining when an FAQ entry can satisfy a user's information need within product search, without disrupting their shopping experience, represents an important challenge. We propose an intent-aware FAQ retrieval system consisting of (1) an intent classifier that predicts when a user's information need can be answered by an FAQ; (2) a reformulation model that rewrites a query into a natural question. Offline evaluation demonstrates that our approach improves Hit@1 by 13% on retrieving ground-truth FAQs, while reducing latency by 95% compared to baseline systems. These improvements are further validated by real user feedback, where 71% of displayed FAQs on top of product search results received explicit positive user feedback. Overall, our findings show promising directions for integrating FAQ retrieval into product search at scale.

Keywords

Cite

@article{arxiv.2306.03411,
  title  = {Generate-then-Retrieve: Intent-Aware FAQ Retrieval in Product Search},
  author = {Zhiyu Chen and Jason Choi and Besnik Fetahu and Oleg Rokhlenko and Shervin Malmasi},
  journal= {arXiv preprint arXiv:2306.03411},
  year   = {2023}
}

Comments

ACL 2023 Industry Track

R2 v1 2026-06-28T10:57:27.110Z