NeuCDCF is a wide-and-deep neural architecture for cross-domain collaborative filtering that jointly learns matrix factorization and deep representations, reporting better performance than prior CDCF models on four real-world datasets.
Title resolution pending
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
cs.IR 2years
2019 2verdicts
UNVERDICTED 2representative citing papers
DSCF is a deep social collaborative filtering model that uses distant neighbors and item-relevant opinions from social networks to improve recommendation accuracy over prior deep models.
citing papers explorer
-
Neural Cross-Domain Collaborative Filtering with Shared Entities
NeuCDCF is a wide-and-deep neural architecture for cross-domain collaborative filtering that jointly learns matrix factorization and deep representations, reporting better performance than prior CDCF models on four real-world datasets.
-
Deep Social Collaborative Filtering
DSCF is a deep social collaborative filtering model that uses distant neighbors and item-relevant opinions from social networks to improve recommendation accuracy over prior deep models.