Multi-granularity Fatigue in Recommendation-Reference-Cited by-同舟云学术

Multi-granularity Fatigue in Recommendation

Published:2022-10-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Information & Knowledge Management
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Author:

Xie Ruobing¹,Ling Cheng¹,Zhang Shaoliang¹,Xia Feng¹,Lin Leyu¹

Affiliation:

1. WeChat, Tencent, Beijing, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3511808.3557651

Reference29 articles.

1. Soft Frequency Capping for Improved Ad Click Prediction in Yahoo Gemini Native

2. Fatigue-Aware Bandits for Dependent Click Models

3. Controllable Multi-Interest Framework for Recommendation

4. Hong Chen , Yudong Chen , Xin Wang , Ruobing Xie , Rui Wang , Feng Xia , and Wenwu Zhu . 2021 a. Curriculum Disentangled Recommendation with Noisy Multi-feedback . Proceedings of NeurIPS. Hong Chen, Yudong Chen, Xin Wang, Ruobing Xie, Rui Wang, Feng Xia, and Wenwu Zhu. 2021a. Curriculum Disentangled Recommendation with Noisy Multi-feedback. Proceedings of NeurIPS.

5. Wanyu Chen , Pengjie Ren , Fei Cai , Fei Sun , and Maarten De Rijke . 2021b. Multi-interest diversification for end-to-end sequential recommendation. TOIS ( 2021 ). Wanyu Chen, Pengjie Ren, Fei Cai, Fei Sun, and Maarten De Rijke. 2021b. Multi-interest diversification for end-to-end sequential recommendation. TOIS (2021).

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