论文标题
cookie：用于电子商务中知识图的对话推荐的数据集
COOKIE: A Dataset for Conversational Recommendation over Knowledge Graphs in E-commerce
论文作者
论文摘要
在这项工作中，我们提出了一个新数据集，以在称为Cookie的电子商务平台中对知识图进行对话建议。数据集是通过亚马逊评论语料库构建的，通过集成用户代理对话和自定义知识图以供推荐。具体来说，我们首先构建一个统一的知识图，并在用户对之间提取关键实体 - 产品对，这些实体是对话的骨架。然后，我们模拟对话的对话，反映了选择首选项目的人类粗到精细过程。拟议的基线和实验表明，我们的数据集能够为会话推荐提供创新的机会。
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.
