Causal Intervention for Leveraging Popularity Bias in Recommendation

Author:

Zhang Yang1,Feng Fuli2,He Xiangnan1,Wei Tianxin1,Song Chonggang3,Ling Guohui3,Zhang Yongdong1

Affiliation:

1. University of Science and Technology of China, Hefei, China

2. National University of Singapore, Singapore, Singapore

3. Tencent Inc., Shenzhen, China

Funder

National Natural Science Foundation of China

National Key Research and Development Program of China

Publisher

ACM

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1. Mitigating Hidden Confounding Effects for Causal Recommendation;IEEE Transactions on Knowledge and Data Engineering;2024-09

2. Bias and Unfairness in Information Retrieval Systems: New Challenges in the LLM Era;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

3. Debiased Recommendation with Noisy Feedback;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

4. Counteracting Duration Bias in Video Recommendation via Counterfactual Watch Time;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

5. Performative Debias with Fair-exposure Optimization Driven by Strategic Agents in Recommender Systems;Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining;2024-08-24

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