1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.IR2024
beeFormer: Bridging the Gap Between Semantic and Interaction Similarity in Recommender Systems
Vojtěch Vančura, Pavel Kordík, Milan Straka
Recommender systems often use text-side information to improve their predictions, especially in cold-start or zero-shot recommendation scenarios, where traditional collaborative fi…
cs.IR2023★ 1 cited
Bridging Offline-Online Evaluation with a Time-dependent and Popularity Bias-free Offline Metric for Recommenders
Petr Kasalický, Rodrigo Alves, Pavel Kordík
The evaluation of recommendation systems is a complex task. The offline and online evaluation metrics for recommender systems are ambiguous in their true objectives. The majority o…