In this work, we present a new dataset for conversational recommendation over knowledge graphs in e-commerce platforms called COOKIE. The dataset is constructed from an Amazon review corpus by integrating both user-agent dialogue and custom knowledge graphs for recommendation. Specifically, we first construct a unified knowledge graph and extract key entities between user--product pairs, which serve as the skeleton of a conversation. Then we simulate conversations mirroring the human coarse-to-fine process of choosing preferred items. The proposed baselines and experiments demonstrate that our dataset is able to provide innovative opportunities for conversational recommendation.
@article{arxiv.2008.09237,
title = {COOKIE: A Dataset for Conversational Recommendation over Knowledge Graphs in E-commerce},
author = {Zuohui Fu and Yikun Xian and Yaxin Zhu and Yongfeng Zhang and Gerard de Melo},
journal= {arXiv preprint arXiv:2008.09237},
year = {2020}
}