Robin Verachtert

According to our database, Robin Verachtert authored at least 9 papers between 2022 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Enhancing Diversity in News Recommendations Increases Click-Through Rates: Insights from an Online Experiment and User Study.

Robin Verachtert, Kim Falk, Christine Bauer

Proceedings of the 34th ACM Conference on User Modeling, Adaptation and Personalization, 2026

2024

A Framework and Toolkit for Testing the Correctness of Recommendation Algorithms.

Lien Michiels, Robin Verachtert, Andres Ferraro, Kim Falk, Bart Goethals

Trans. Recomm. Syst., March, 2024

2023

Temporal dynamics in online recommender systems

Robin Verachtert

PhD thesis, 2023

How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News.

Lien Michiels, Jorre T. A. Vannieuwenhuyze, Jens Leysen, Robin Verachtert, Annelien Smets, Bart Goethals

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

The Impact of a Popularity Punishing Hyperparameter on ItemKNN Recommendation Performance.

Robin Verachtert, Jeroen Craps, Lien Michiels, Bart Goethals

Proceedings of the Advances in Information Retrieval, 2023

2022

Are We Forgetting Something? Correctly Evaluate a Recommender System With an Optimal Training Window.

Robin Verachtert, Lien Michiels, Bart Goethals

Proceedings of the Perspectives on the Evaluation of Recommender Systems Workshop 2022 co-located with the 16th ACM Conference on Recommender Systems (RecSys 2022), 2022

RecPack: An(other) Experimentation Toolkit for Top-N Recommendation using Implicit Feedback Data.

Lien Michiels, Robin Verachtert, Bart Goethals

Proceedings of the RecSys '22: Sixteenth ACM Conference on Recommender Systems, Seattle, WA, USA, September 18, 2022

Abstract: Should Algorithm Evaluation Extend to Testing? We Think So.

Lien Michiels, Robin Verachtert, Kim Falk, Bart Goethals

Proceedings of the Perspectives on the Evaluation of Recommender Systems Workshop 2022 co-located with the 16th ACM Conference on Recommender Systems (RecSys 2022), 2022

A Neighbourhood-based Location- and Time-aware Recommender System.

Len Feremans, Robin Verachtert, Bart Goethals

Proceedings of the 5th Workshop on Online Recommender Systems and User Modeling co-located with the 16th ACM Conference on Recommender Systems, 2022