PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation-Reference-Cited by-同舟云学术

PEAR: Personalized Re-ranking with Contextualized Transformer for Recommendation

Published:2022-04-25 Issue: Volume: Page:
ISSN:
Container-title:Companion Proceedings of the Web Conference 2022
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Author:

Li Yi¹,Zhu Jieming²,Liu Weiwen²,Su Liangcai¹,Cai Guohao²,Zhang Qi²,Tang Ruiming²,Xiao Xi¹,He Xiuqiang²

Affiliation:

1. Tsinghua University, China

2. Huawei Noah's Ark Lab, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3487553.3524208

Reference28 articles.

1. Learning a Deep Listwise Context Model for Ranking Refinement

2. 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).

3. Learning to rank

4. Behavior sequence transformer for e-commerce recommendation in Alibaba

5. Temporal Hierarchical Attention at Category- and Item-Level for Micro-Video Click-Through Prediction

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