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cs.IR2026
Learning Sparse Representations of Multimodal Content for Enhanced Cold Item Recommendation
Gregor Meehan, Johan Pauwels
The scale and rapid growth of item catalogs in modern digital platforms present significant challenges to recommender system (RS) practitioners. Most RSs use embedding similarity t…
cs.IR2026
Sparse Contrastive Learning for Content-Based Cold Item Recommendation
Gregor Meehan, Johan Pauwels
Item cold-start is a pervasive challenge for collaborative filtering (CF) recommender systems. Existing methods often train cold-start models by mapping auxiliary item content, suc…
cs.IR2025
On Inherited Popularity Bias in Cold-Start Item Recommendation
Gregor Meehan, Johan Pauwels
Collaborative filtering (CF) recommender systems struggle with making predictions on unseen, or 'cold', items. Systems designed to address this challenge are often trained with sup…