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Today's research in recommender systems is largely based on experimental designs that are static in a sense that they do not consider potential longitudinal effects of providing recommendations to users.
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RecSim: A Configurable Simulation Platform for Recommender Systems
E. Ie, C. Hsu, M. Mladenov, V. Jain, S. Narvekar, J. Wang, R. Wu, and C. Boutilier · 2019
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Measuring the business value of recommender systems
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How Do Recommender Systems Affect Sales Diversity? A Cross-Category Investigation via Randomized Field Experiment
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PyRecGym: A reinforcement learning gym for recommender systems
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Multistakeholder recommendation: Survey and research directions
H. Abdollahpouri, G. Adomavicius, R. Burke, I. Guy, D. Jannach, T. Kamishima, J. Krasnodebski, and L. Pizzato · 2020
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S. Leitner and F. Wall · 2015
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Recommendations with a purpose
D. Jannach and G. Adomavicius · 2016
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Context-aware recommender systems in mobile environment: On the road of future research
I. B. Sassi, S. Mellouli, and S. B. Yahia · 2017
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How algorithmic confounding in recommendation systems increases homogeneity and decreases utility
A. J. Chaney, B. M. Stewart, and B. E. Engelhardt · 2018
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D. Rohde, S. Bonner, T. Dunlop, F. Vasile, and A. Karatzoglou · 2018
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SIREN: A simulation framework for understanding the effects of recommender systems in online news environments
D. Bountouridis, J. Harambam, M. Makhortykh, M. Marrero, N. Tintarev, and C. Hauff · 2019
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Exploring longitudinal effects of session-based recommendations
A. Ferraro, D. Jannach, and X. Serra · 2020
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Keeping dataset biases out of the simulation: A debiased simulator for reinforcement learning based recommender systems
J. Huang, H. Oosterhuis, M. de Rijke, and H. van Hoof · 2020
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Agent-based Computational Economics in Management Accounting Research: Opportunities and Difficulties
F. Wall and S. Leitner · 2020
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Consumption and performance: Understanding longitudinal dynamics of recommender systems via an agent-based simulation framework
J. Zhang, G. Adomavicius, A. Gupta, and W. Ketter · 2020
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RecSim NG: Toward Principled Uncertainty Modeling for Recommender Ecosystems
M. Mladenov, C. Hsu, E. I. Vihan Jain, C. Colby, N. Mayoraz, H. Pham, D. Tran, I. Vendrov, and C. Boutilier · 2021
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Longitudinal impact of preference biases on recommender systems’ performance
M. Zhou, J. Zhang, and G. Adomavicius · 2021
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