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The progress of recommender systems is hampered mainly by evaluation as it requires real-time interactions between humans and systems, which is too laborious and expensive.
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Recsim: A Configurable Simulation Platform for Recommender Systems
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Advances and Challenges in Conversational Recommender Systems: A Survey
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A Survey on Conversational Recommender Systems
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RecSys 2021 Tutorial on Conversational Recommendation: Formulation, Methods, and Evaluation. In RecSys ’21 . 842–844
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Durecdial 2.0: A bilingual parallel corpus for conversational recommendation
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Information Management in Smart Cities: Turning end users’ views into multi-item scale development, validation, and policy-making recommendations
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Open Bandit Dataset and Pipeline: Towards Realistic and Reproducible Off-Policy Evaluation. In NeurIPS ’21
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Counterfactual Data-Augmented Sequential Recommendation. In SIGIR ’21 . 347–356
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Causal Intervention for Leveraging Popularity Bias in Recommendation. In SIGIR ’21 . 11–20
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CIRS: Bursting Filter Bubbles by Counterfactual Interactive Recommender System
Chongming Gao, Wenqiang Lei, Jiawei Chen, Shiqi Wang, Xiangnan He, Shijun Li, Biao Li, Yuan Zhang, and Peng Jiang. 2022 · 2022
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User-Centric Conversational Recommendation with Multi-Aspect User Modeling
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Variational Reasoning about User Preferences for Conversational Recommendation
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Who Are the Best Adopters? User Selection Model for Free Trial Item Promotion
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Multiple Choice Questions Based Multi-Interest Policy Learning for Conversational Recommendation (WWW ’22) . 2153–2162
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C2-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender System
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Interactive Path Reasoning on Graph for Conversational Recommendation. In KDD ’20 . 2073–2083
Wenqiang Lei, Gangyi Zhang, Xiangnan He, Yisong Miao, Xiang Wang, Liang Chen, and Tat-Seng Chua. 2020b · 2083
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