Tag: collaborative filtering

Researchers at a Chinese power grid enterprise have built a recommendation system that combines knowledge graphs with dynamic employee personas ...

Researchers have introduced RPGCN, a relation-preserving graph convolutional network that combats oversmoothing and relational dilution to outperform state-of-the-art baselines across ...

Researchers at the Vellore Institute of Technology have built NEXUS-Rec, a five-signal neural recommender that outperforms strong baselines on MovieLens ...

A University of Cagliari study comparing recommendation algorithms across four educational datasets finds that the most accurate course recommenders are ...

Researchers have built a hybrid recommender system that combines a deep denoising graph convolutional autoencoder, demographic side information, and learning ...

Researchers have developed SAGMR, a graph-learning recommender that explicitly models artistic style to improve digital media art suggestions, with the ...

A comprehensive review in Artificial Intelligence Review argues that reinforcement learning can overcome the static limitations of traditional recommender systems, ...

Researchers have developed RecGP, a gradient penalty method that crafts transferable adversarial fake users by steering them toward flat regions ...

A systematic review of 135 studies reveals that AI recommender systems succeed in online marketplaces only when algorithmic performance, consumer ...

Recommender systems trained across users' own devices promise to keep private interaction histories off central servers, but a persistent tension ...