Tag: recommender systems

A new recommender model called COMPASS learns a user-specific allocation over spectral bands instead of a fixed truncation rank, improving ...

A new method called CEGDSR combines global and disentangled intent-aware representations to improve sequential recommendation, outperforming several strong baselines on ...

A new recommender framework replaces single user and item embeddings with shared multi-aspect pools, improving accuracy across six datasets.

A new open-access study in Discover Computing presents CMCBI, a recommendation framework that aligns corporate financial signals with consumer behavior ...

Researchers have introduced HOFA, a contrastive learning framework that mines triangular motifs in social networks and aligns embedding features to ...

Researchers propose MELRec, a modular end-to-end framework that combines GPT-2 semantic encoding with lightweight behavior modeling and achieved leading or ...

A new semantic-guided graph attention framework improves rating prediction and ranking on Amazon cross-domain recommendation pairs while showing controlled but ...

A dual-channel machine-learning framework combined sentiment, academic performance and engagement data to predict educational AI adoption, learning gains and personalized ...

Researchers have introduced ε-iFair, the first job recommendation algorithm with a tunable ε-individual fairness guarantee that also keeps recommendations calibrated ...

A new framework called CT-IDR combines recency-aware preference encoding, signed social influence propagation, and causal debiasing to improve both accuracy ...