COOKIE: A Dataset for Conversational Recommendation over Knowledge Graphs in E-commerce
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Abstract (arXiv)
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.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Aug 2020.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 1; 2024: 1; 2025: 1.
6 papers.
- 2021Advances and Challenges in Conversational Recommender Systems: A Surveycited by 118
- 2021Efficient Non-Sampling Knowledge Graph Embeddingcited by 14
- 2024Simulating Task-Oriented Dialogues with State Transition Graphs and Large Language Modelscited by 6
- 2022INSPIRED2: An Improved Dataset for Sociable Conversational Recommendationcited by 4
- 2023Salespeople vs SalesBot: Exploring the Role of Educational Value in Conversational Recommender Systemscited by 1
- 2025PSCon: Product Search Through Conversationscited by 1
- 2025PSCon: Product Search Through Conversations19 Feb 2025
- 2024Simulating Task-Oriented Dialogues with State Transition Graphs and Large Language Models23 Apr 2024
- 2023Salespeople vs SalesBot: Exploring the Role of Educational Value in Conversational Recommender Systems26 Oct 2023
- 2022INSPIRED2: An Improved Dataset for Sociable Conversational Recommendation8 Aug 2022
- 2021Efficient Non-Sampling Knowledge Graph Embedding21 Apr 2021
- 2021Advances and Challenges in Conversational Recommender Systems: A Survey23 Jan 2021