39 citations · 45 across the 11 of their papers we have counts for
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cs.IR2023★ 39 cited
Formalizing Multimedia Recommendation through Multimodal Deep Learning
Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo +3
Recommender systems (RSs) offer personalized navigation experiences on online platforms, but recommendation remains a challenging task, particularly in specific scenarios and domai…
cs.IR2023
On Popularity Bias of Multimodal-aware Recommender Systems: a Modalities-driven Analysis
Daniele Malitesta, Giandomenico Cornacchia, Claudio Pomo +1
Multimodal-aware recommender systems (MRSs) exploit multimodal content (e.g., product images or descriptions) as items' side information to improve recommendation accuracy. While m…