Disentangling interest and conformity for eliminating popularity bias in session-based recommendation

Author:

Liu Qidong,Tian Feng,Zheng Qinghua,Wang Qianying

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Innovative Research Group Project of the National Natural Science Foundation of China

Innovation Research Team of Ministry of Education, China

Project of China Knowledge Center for Engineering Science and Technology

Project of Chinese Academy of engineering “The Online and Offline Mixed Educational Service System for ‘The Belt and Road’ Training in MOOC China”

“LENOVO-XJTU” Intelligent Industry Joint Laboratory Project

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. EqBal-RS: Mitigating popularity bias in recommender systems;Journal of Intelligent Information Systems;2023-11-07

2. Diffusion Augmentation for Sequential Recommendation;Proceedings of the 32nd ACM International Conference on Information and Knowledge Management;2023-10-21

3. STRec: Sparse Transformer for Sequential Recommendations;Proceedings of the 17th ACM Conference on Recommender Systems;2023-09-14

4. AutoAssign+: Automatic Shared Embedding Assignment in streaming recommendation;Knowledge and Information Systems;2023-08-13

5. CIPL: Counterfactual Interactive Policy Learning to Eliminate Popularity Bias for Online Recommendation;IEEE Transactions on Neural Networks and Learning Systems;2023

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