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2020 – today
- 2024
[j1]Lien Michiels
, Robin Verachtert, Andres Ferraro, Kim Falk, Bart Goethals:
A Framework and Toolkit for Testing the Correctness of Recommendation Algorithms. Trans. Recomm. Syst. 2(1): 4:1-4:45 (2024)- 2023
- [b1]Robin Verachtert:
Temporal dynamics in online recommender systems. University of Antwerp, Belgium, 2023 - [c6]Robin Verachtert, Jeroen Craps, Lien Michiels, Bart Goethals:
The Impact of a Popularity Punishing Hyperparameter on ItemKNN Recommendation Performance. ECIR (2) 2023: 646-654 - [c5]Lien Michiels, Jorre T. A. Vannieuwenhuyze, Jens Leysen, Robin Verachtert, Annelien Smets, Bart Goethals:
How Should We Measure Filter Bubbles? A Regression Model and Evidence for Online News. RecSys 2023: 640-651 - 2022
- [c4]Len Feremans, Robin Verachtert, Bart Goethals:
A Neighbourhood-based Location- and Time-aware Recommender System. ORSUM@RecSys 2022 - [c3]Lien Michiels, Robin Verachtert, Kim Falk, Bart Goethals:
Abstract: Should Algorithm Evaluation Extend to Testing? We Think So. Perspectives@RecSys 2022 - [c2]Lien Michiels, Robin Verachtert, Bart Goethals:
RecPack: An(other) Experimentation Toolkit for Top-N Recommendation using Implicit Feedback Data. RecSys 2022: 648-651 - [c1]Robin Verachtert, Lien Michiels, Bart Goethals:
Are We Forgetting Something? Correctly Evaluate a Recommender System With an Optimal Training Window. Perspectives@RecSys 2022
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