Methodologies to evaluate recommender systems

Source
Antwerp, University of Antwerp, Faculty of Science, Department of Computer Science, 2024,xviii, 244 p.

A framework and toolkit for testing the correctness of recommendation algorithms

Source
ACM Transactions on Recommender Systems - ISSN 2770-6699-2:1 (2024) p. 1-45
Author(s)

How should we measure filter bubbles? A regression model and evidence for online news

Source
RecSys '23 : proceedings of the 17th ACM Conference on Recommender Systems, September 18-22, 2023, Singapore- () p. 640-651
Author(s)

Artificial Intelligence and Machine Learning : 34th Joint Benelux Conference, BNAIC/Benelearn 2022, November 7–9, 2022, Mechelen, Belgium

Source
Cham, Springer, 2023,179 p.
Author(s)

The impact of a popularity punishing hyperparameter on ItemKNN recommendation performance

Source
Lecture notes in computer science-13981 (2023) p. 646-654
Author(s)