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CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation [article]

Shengyu Zhang, Dong Yao, Zhou Zhao, Tat-seng Chua, Fei Wu
2021 arXiv   pre-print
The results demonstrate that the proposed CauseRec outperforms state-of-the-art sequential recommenders by learning accurate and robust user representations.  ...  Recent advances in sequential recommenders have convincingly demonstrated high capability in extracting effective user representations from the given behavior sequences.  ...  In this paper, we propose Counterfactual U ser Sequence Synthesis for Sequential Recommendation, abbreviated as CauseRec.  ... 
arXiv:2109.05261v1 fatcat:ml4l2scfvfgh5lbdbh7r6blawq