From Variability to Stability: Advancing RecSys Benchmarking Practices

no code implementations • 15 Feb 2024 • Valeriy Shevchenko, Nikita Belousov, Alexey Vasilev, Vladimir Zholobov, Artyom Sosedka, Natalia Semenova, Anna Volodkevich, Andrey Savchenko, Alexey Zaytsev

In the rapidly evolving domain of Recommender Systems (RecSys), new algorithms frequently claim state-of-the-art performance based on evaluations over a limited set of arbitrarily selected datasets.

Benchmarking Collaborative Filtering +1

Synthetic Data-Based Simulators for Recommender Systems: A Survey

no code implementations • 22 Jun 2022 • Elizaveta Stavinova, Alexander Grigorievskiy, Anna Volodkevich, Petr Chunaev, Klavdiya Bochenina, Dmitry Bugaychenko

This survey aims at providing a comprehensive overview of the recent trends in the field of modeling and simulation (M&S) of interactions between users and recommender systems and applications of the M&S to the performance improvement of industrial recommender engines.

Recommendation Systems