FedDMF: Privacy-Preserving User Attribute Prediction using Deep Matrix Factorization.
Ming CheungPublished in: CoRR (2023)
Keyphrases
- privacy preserving
- matrix factorization
- collaborative filtering
- recommender systems
- item recommendation
- privacy preserving data mining
- user privacy
- vertically partitioned data
- factorization methods
- privacy preservation
- low rank
- missing data
- sensitive information
- data privacy
- private information
- privacy sensitive
- privacy concerns
- end users
- negative matrix factorization
- multi party
- preserving privacy
- data publishing
- user preferences
- horizontally partitioned data
- secure multiparty computation
- nonnegative matrix factorization
- attribute values
- differential privacy
- private data
- tensor factorization
- privacy protection
- user interaction
- sensitive data
- latent factors
- third party
- knowledge discovery
- recommendation systems
- social media
- support vector