Preventing the Popular Item Embedding Based Attack in Federated Recommendations.
Jun ZhangHuan LiDazhong RongYan ZhaoKe ChenLidan ShouPublished in: ICDE (2024)
Keyphrases
- making recommendations
- user preferences
- personalized recommendation
- cold start problem
- recommender systems
- item recommendation
- cold start
- recommendation algorithms
- hybrid recommendation
- user ratings
- collaborative filtering
- latent factor models
- countermeasures
- vector space
- personalized recommender systems
- matrix factorization
- digital libraries
- recommendation systems
- trust relationships
- rating prediction
- collaborative recommendation
- power analysis
- malicious users
- data sets
- data hiding
- collaborative recommender systems
- search engine
- digital images
- distributed systems
- personal preferences
- information security
- graph embedding
- nonlinear dimensionality reduction