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Found 2 papers, 1 papers with code
MultiCBR: Multi-view Contrastive Learning for Bundle Recommendation
It does, however, have two limitations: 1) the two-view formulation does not fully exploit all the heterogeneous relations among users, bundles and items; and 2) the "early contrast and late fusion" framework is less effective in capturing user preference and difficult to generalize to multiple views.
Item-based Collaborative Filtering with BERT
In e-commerce, recommender systems have become an indispensable part of helping users explore the available inventory.
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