CA-PDBPR: category-aware privacy preserving POI recommendation using decentralized Bayesian personalized ranking.
Qinyun GaoShenbao YuBilian ChenLangcai CaoPublished in: Appl. Intell. (2024)
Keyphrases
- privacy preserving
- personalized ranking
- item recommendation
- bayesian analysis
- implicit feedback
- tag recommendation
- user preferences
- matrix factorization
- collaborative filtering
- recommender systems
- user generated
- privacy preserving data mining
- privacy preservation
- vertically partitioned data
- user feedback
- multi party
- user behavior
- recommendation systems
- personalized recommendation
- data privacy
- privacy sensitive
- private information
- secure multiparty computation
- computationally feasible
- data sparsity
- cold start
- horizontally partitioned data
- privacy concerns
- privacy protection
- sensitive information
- location based services
- user interests
- differential privacy
- eye tracking
- peer to peer
- web search
- scalar product
- search result
- website
- user generated content
- user experience
- user profiles
- contextual information
- user interaction
- mobile devices