A Privacy-Preserving and Identity-Based Personalized Recommendation Scheme for Encrypted Tasks in Crowdsourcing.
Hui YinYinqiao XiongTiantian DengHua DengPeidong ZhuPublished in: IEEE Access (2019)
Keyphrases
- privacy preserving
- personalized recommendation
- horizontally partitioned data
- privacy preserving data mining
- vertically partitioned data
- privacy preservation
- user feedback
- multi party
- data privacy
- private information
- privacy concerns
- user interests
- privacy sensitive
- privacy protection
- recommender systems
- sensitive information
- sensitive data
- scalar product
- privacy issues
- recommendation systems
- key management
- third party
- user preferences
- collaborative filtering