References#
Mukund Deshpande and George Karypis. Item-based top-N Recommendation Algorithms. ACM Trans. Inf. Syst., 22(1):143–177, January 2004. doi:10.1145/963770.963776.
Michael Ekstrand, Michael Ludwig, Joseph A. Konstan, and John Riedl. Rethinking the Recommender Research Ecosystem: Reproducibility, Openness, and LensKit. In Proceedings of the 5th ACM Conference on Recommender Systems, 133–140. ACM, 2011. doi:10.1145/2043932.2043958.
Michael D Ekstrand. LensKit for Python: Next-Generation Software for Recommender System Experiments. In Proceedings of the 29th ACM International Conference on Information and Knowledge Management. 2020. doi:10.1145/3340531.3412778.
Michael D Ekstrand and Joseph A Konstan. Recommender Systems Notation. Technical Report 177, Boise State University, 2019. doi:10.18122/cs_facpubs/177/boisestate.
Prem Gopalan, Jake M Hofman, and David M Blei. Scalable Recommendation with Poisson Factorization. arXiv:1311.1704 [cs, stat], November 2013. arXiv:1311.1704.
Y Hu, Y Koren, and C Volinsky. Collaborative Filtering for Implicit Feedback Datasets. In 2008 Eighth IEEE International Conference on Data Mining, 263–272. ieeexplore.ieee.org, December 2008. doi:10.1109/ICDM.2008.22.
Kalervo Järvelin and Jaana Kekäläinen. Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems, 20(4):422–446, October 2002. doi:10.1145/582415.582418.
Paul B Kantor and Ellen Voorhees. Report on the TREC-5 Confusion Track. In The Fifth Text REtrieval Conference (TREC-5). October 1997.
Alistair Moffat and Justin Zobel. Rank-Biased Precision for Measurement of Retrieval Effectiveness. Transactions on Information Systems, 27(1):2:1–27, December 2008. doi:10.1145/1416950.1416952.
Yan-Martin Tamm, Rinchin Damdinov, and Alexey Vasilev. Quality Metrics in Recommender Systems: Do We Calculate Metrics Consistently? In RecSys '21, 708–713. New York, NY, USA, September 2021. Association for Computing Machinery. doi:10.1145/3460231.3478848.
Yunhong Zhou, Dennis Wilkinson, Robert Schreiber, and Rong Pan. Large-Scale Parallel Collaborative Filtering for the Netflix Prize. In Algorithmic Aspects in Information and Management, 337–348. Springer Berlin Heidelberg, 2008. doi:10.1007/978-3-540-68880-8_32.