Federated Multi-view Matrix Factorization for Personalized Recommendations.
Adrian FlanaganWere OyomnoAlexander GrigorievskiyKuan Eeik TanSuleiman A. KhanMuhammad Ammad-ud-dinPublished in: ECML/PKDD (2) (2020)
Keyphrases
- multi view
- matrix factorization
- personalized recommendation
- collaborative filtering
- recommender systems
- multiple views
- recommendation systems
- d objects
- data sparsity
- three dimensional
- user preferences
- negative matrix factorization
- semi supervised
- transfer learning
- learning to rank
- information overload
- user interests
- user feedback
- recommendation algorithms
- user ratings
- factorization method
- user profiles