Federated matrix factorization for privacy-preserving recommender systems.
Yongjie DuDeyun ZhouYu XieJiao ShiMaoguo GongPublished in: Appl. Soft Comput. (2021)
Keyphrases
- privacy preserving
- matrix factorization
- recommender systems
- collaborative filtering
- privacy preserving data mining
- low rank
- privacy preservation
- nonnegative matrix factorization
- vertically partitioned data
- multi party
- data privacy
- data sparsity
- privacy concerns
- cold start problem
- private information
- digital libraries
- sensitive data
- scalar product
- probabilistic matrix factorization
- sensitive information
- implicit feedback
- user preferences
- cold start
- factorization methods
- item recommendation
- privacy sensitive
- data sources
- horizontally partitioned data
- face recognition