Reinforcement Re-ranking with 2D Grid-based Recommendation Panels-Reference-Cited by-同舟云学术

Reinforcement Re-ranking with 2D Grid-based Recommendation Panels

Published:2023-11-26 Issue: Volume: Page:
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Container-title:Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region
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Author:

Chen Sirui¹^ORCID,Zhang Xiao²^ORCID,Chen Xu²^ORCID,Li Zhiyu³^ORCID,Wang Yuan³^ORCID,Lin Quan³^ORCID,Xu Jun²^ORCID

Affiliation:

1. School of Information, Renmin University of China, China

2. Gaoling School of AI (GSAI), Renmin University of China, China

3. Alibaba Group, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3624918.3625311

Reference24 articles.

1. Irwan Bello , Sayali Kulkarni , Sagar Jain , Craig Boutilier , Ed Chi, Elad Eban , Xiyang Luo, Alan Mackey, and Ofer Meshi. 2018 . Seq2slate: Re-ranking and slate optimization with RNNs . arXiv preprint arXiv:1810.02019 (2018). Irwan Bello, Sayali Kulkarni, Sagar Jain, Craig Boutilier, Ed Chi, Elad Eban, Xiyang Luo, Alan Mackey, and Ofer Meshi. 2018. Seq2slate: Re-ranking and slate optimization with RNNs. arXiv preprint arXiv:1810.02019 (2018).

2. Reinforcement Mechanism Design for Fraudulent Behaviour in e-Commerce

3. Controllable Multi-Objective Re-ranking with Policy Hypernetworks

4. Towards Long-term Fairness in Recommendation

5. Debiasing Grid-based Product Search in E-commerce

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