Cross-domain recommendation for cold-start users via neighborhood based feature mapping

X Wang, Z Peng, S Wang, PS Yu, W Fu… - Database Systems for …, 2018 - Springer
Abstract Traditional Collaborative Filtering (CF) models mainly focus on predicting a user's
preference to the items in a single domain such as the movie domain or the music domain. A …

Cross-Domain Recommendation for Cold-Start Users via Neighborhood Based Feature Mapping

X Wang, Z Peng, S Wang, PS Yu, W Fu… - … Conference on Database …, 2018 - dl.acm.org
Abstract Traditional Collaborative Filtering (CF) models mainly focus on predicting a user's
preference to the items in a single domain such as the movie domain or the music domain. A …

[PDF][PDF] Cross-Domain Recommendation for Cold-Start Users via Neighborhood Based Feature Mapping

X Wang, Z Peng, S Wang, PS Yu, W Fu… - arXiv preprint arXiv …, 2018 - researchgate.net
Collaborative Filtering (CF) is a widely adopted technique in recommender systems.
Traditional CF models mainly focus on predicting a user's preference to the items in a single …

Cross-Domain Recommendation for Cold-Start Users via Neighborhood Based Feature Mapping

W Fu, X Hong - Springer
Traditional Collaborative Filtering (CF) models mainly focus on predicting a user's
preference to the items in a single domain such as the movie domain or the music domain. A …

Cross-Domain Recommendation for Cold-Start Users via Neighborhood Based Feature Mapping

X Wang, Z Peng, S Wang, PS Yu, W Fu… - arXiv preprint arXiv …, 2018 - arxiv.org
Collaborative Filtering (CF) is a widely adopted technique in recommender systems.
Traditional CF models mainly focus on predicting a user's preference to the items in a single …

Cross-Domain Recommendation for Cold-Start Users via Neighborhood Based Feature Mapping

X Wang, Z Peng, S Wang, PS Yu, W Fu… - arXiv e …, 2018 - ui.adsabs.harvard.edu
Collaborative Filtering (CF) is a widely adopted technique in recommender systems.
Traditional CF models mainly focus on predicting a user's preference to the items in a single …