Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation-Reference-Cited by-同舟云学术

Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation

Published:2023-09-14 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 17th ACM Conference on Recommender Systems
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Author:

Pan Yunzhu¹^ORCID,Gao Chen²^ORCID,Chang Jianxin³^ORCID,Niu Yanan³^ORCID,Song Yang³^ORCID,Gai Kun⁴^ORCID,Jin Depeng²^ORCID,Li Yong²^ORCID

Affiliation:

1. School of Information and Software Engineering, University of Electronic Science and Technology of China, China

2. Beijing National Research Center for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, China

3. Beijing Kuaishou Technology Co., Ltd., China

4. Unaffiliated, China

Funder

the National Natural Science Foundation of China

the National Key Research and Development Program of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3604915.3608814

Reference49 articles.

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3. Yue Cao XiaoJiang Zhou Jiaqi Feng Peihao Huang Yao Xiao Dayao Chen and Sheng Chen. 2022. Sampling Is All You Need on Modeling Long-Term User Behaviors for CTR Prediction. In CIKM. Yue Cao XiaoJiang Zhou Jiaqi Feng Peihao Huang Yao Xiao Dayao Chen and Sheng Chen. 2022. Sampling Is All You Need on Modeling Long-Term User Behaviors for CTR Prediction. In CIKM.

4. Controllable Multi-Interest Framework for Recommendation

5. User-Aware Multi-Interest Learning for Candidate Matching in Recommenders

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