USST: A two-phase privacy-preserving framework for personalized recommendation with semi-distributed training.
Yipeng ZhouJun LiuJessie Hui WangJilong WangGuanfeng LiuDi WuChao LiShui YuPublished in: Inf. Sci. (2022)
Keyphrases
- privacy preserving
- multi party
- partitioned data
- data privacy
- privacy preserving data mining algorithms
- privacy preservation
- horizontally partitioned
- horizontally partitioned data
- privacy sensitive
- privacy preserving data mining
- privacy guarantees
- vertically partitioned data
- personalized recommendation
- distributed systems
- privacy concerns
- sensitive data
- social networks
- private data
- collaborative filtering
- recommender systems