PIER: Permutation-Level Interest-Based End-to-End Re-ranking Framework in E-commerce-Reference-Cited by-同舟云学术

PIER: Permutation-Level Interest-Based End-to-End Re-ranking Framework in E-commerce

Published:2023-08-04 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
language:
Short-container-title:

Author:

Shi Xiaowen¹^ORCID,Yang Fan¹^ORCID,Wang Ze¹^ORCID,Wu Xiaoxu¹^ORCID,Guan Muzhi¹^ORCID,Liao Guogang¹^ORCID,Yongkang Wang¹^ORCID,Wang Xingxing¹^ORCID,Wang Dong¹^ORCID

Affiliation:

1. Meituan, Beijing, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3580305.3599886

Reference29 articles.

1. Learning a Deep Listwise Context Model for Ranking Refinement

2. Areej Alsini , Du Q Huynh , and Amitava Datta . 2020. Hit ratio: An evaluation metric for hashtag recommendation. arXiv preprint arXiv:2010.01258 ( 2020 ). Areej Alsini, Du Q Huynh, and Amitava Datta. 2020. Hit ratio: An evaluation metric for hashtag recommendation. arXiv preprint arXiv:2010.01258 (2020).

3. 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).

4. Sampling Is All You Need on Modeling Long-Term User Behaviors for CTR Prediction

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Non-autoregressive Generative Models for Reranking Recommendation;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24