Re‐ranking with multiple objective optimization in recommender system
Author:
Affiliation:
1. School of Computer Science and Engineering Central South University Changsha 410083 China
2. School of Computer Science Guangzhou University Guangzhou 510006 China
3. Department of Computer and Information Sciences Fordham University NY 10458 USA
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Natural Science Foundation of Guangdong Province
Publisher
Wiley
Subject
Electrical and Electronic Engineering
Link
https://onlinelibrary.wiley.com/doi/pdf/10.1002/ett.4398
Reference37 articles.
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3. LiC FengH deRijkeM.Cascading hybrid bandits: online learning to rank for relevance and diversity. Proceedings of the 14th ACM Conference on Recommender Systems; 2020:33‐42.
4. ZolaktafZ BabanezhadR PottingerR.A generic top‐n recommendation framework for trading‐off accuracy novelty and coverage. Proceedings of the 34th IEEE International Conference on Data Engineering; 2018:149‐160.
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