Pursuing Optimal Trade-Off Solutions in Multi-Objective Recommender Systems

Author:

Paparella Vincenzo1

Affiliation:

1. Information Systems laboratory, Politecnico di Bari, Italy

Publisher

ACM

Reference23 articles.

1. Himan Abdollahpouri , Mehdi Elahi , Masoud Mansoury , Shaghayegh Sahebi , Zahra Nazari , Allison Chaney , and Babak Loni . 2021 . MORS 2021: 1st Workshop on Multi-Objective Recommender Systems. In RecSys ’21: Fifteenth ACM Conference on Recommender Systems , Amsterdam, The Netherlands , 27 September 2021 - 1 October 2021, Humberto Jesús Corona Pampín, Martha A. Larson, Martijn C. Willemsen, Joseph A. Konstan, Julian J. McAuley, Jean Garcia-Gathright, Bouke Huurnink, and Even Oldridge (Eds.). ACM, 787–788. https://doi.org/10.1145/3460231.3470936 Himan Abdollahpouri, Mehdi Elahi, Masoud Mansoury, Shaghayegh Sahebi, Zahra Nazari, Allison Chaney, and Babak Loni. 2021. MORS 2021: 1st Workshop on Multi-Objective Recommender Systems. In RecSys ’21: Fifteenth ACM Conference on Recommender Systems, Amsterdam, The Netherlands, 27 September 2021 - 1 October 2021, Humberto Jesús Corona Pampín, Martha A. Larson, Martijn C. Willemsen, Joseph A. Konstan, Julian J. McAuley, Jean Garcia-Gathright, Bouke Huurnink, and Even Oldridge (Eds.). ACM, 787–788. https://doi.org/10.1145/3460231.3470936

2. Hirotogu Akaike . 1998. Information Theory and an Extension of the Maximum Likelihood Principle . Springer New York , New York, NY , 199–213. https://doi.org/10.1007/978-1-4612-1694-0_15 Hirotogu Akaike. 1998. Information Theory and an Extension of the Maximum Likelihood Principle. Springer New York, New York, NY, 199–213. https://doi.org/10.1007/978-1-4612-1694-0_15

3. Elliot: A Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

4. P-MOIA-RS: a multi-objective optimization and decision-making algorithm for recommendation systems

5. Are we really making much progress? A worrying analysis of recent neural recommendation approaches

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