References

[DK04]

Mukund Deshpande and George Karypis. Item-based top-n recommendation algorithms. ACM Trans. Inf. Syst., 22(1):143–177, jan 2004. URL: https://doi.org/10.1145/963770.963776, doi:10.1145/963770.963776.

[MVG22]

Lien Michiels, Robin Verachtert, and Bart Goethals. Recpack: an(other) experimentation toolkit for top-n recommendation using implicit feedback data. In Proceedings of the 16th ACM Conference on Recommender Systems, RecSys '22, 648–651. New York, NY, USA, 2022. Association for Computing Machinery. URL: https://doi.org/10.1145/3523227.3551472, doi:10.1145/3523227.3551472.

[Sun23]

Aixin Sun. Take a fresh look at recommender systems from an evaluation standpoint. In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR ’23. ACM, July 2023. URL: http://dx.doi.org/10.1145/3539618.3591931, doi:10.1145/3539618.3591931.