Full-stage Diversified Recommendation: Large-scale Online Experiments in Short-video Platform
Author:
Affiliation:
1. Shenzhen International Graduate School, Tsinghua University, Shenzhen, China
2. School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu, China
3. Tsinghua University, Beijing, China
Funder
National Natural Science Foundation of China
National Key Research and Development Program of China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3589334.3648144
Reference62 articles.
1. Learning a Deep Listwise Context Model for Ranking Refinement
2. Azin Ashkan, Branislav Kveton, Shlomo Berkovsky, and Zheng Wen. 2015. Optimal greedy diversity for recommendation. In Twenty-Fourth International Joint Conference on Artificial Intelligence.
3. CaSMoS
4. 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. arXiv preprint arXiv:2205.10249 (2022).
5. The use of MMR, diversity-based reranking for reordering documents and producing summaries
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