Rank-Constrained Deep Matrix Completion for Group Recommendation

ArXi:2606.01948v1 Announce Type: cross The growing popularity of group activities has increased the need for methods that provide recommendations to groups of users given their individual preferences. Many existing group recommender systems rely on aggregating individual user preferences, but they often struggle with high-dimensional and highly sparse rating data commonly found in real-world scenarios.