Detecting Anomalous Ratings Using Matrix Factorization for Recommender Systems.
Zhihai YangZhongmin CaiXinyuan ChenPublished in: WAIM (2) (2016)
Keyphrases
- matrix factorization
- detecting anomalous
- recommender systems
- collaborative filtering
- cold start problem
- intrusion detection
- anomaly detection
- netflix prize
- user preferences
- cold start
- user ratings
- rating prediction
- low rank
- latent factor models
- network traffic
- data sparsity
- collaborative filtering algorithms
- personalized recommendation
- factorization methods
- active user
- recommendation algorithms
- implicit feedback
- item recommendation
- rating matrix
- user profiles
- negative matrix factorization
- nonnegative matrix factorization
- stochastic gradient descent
- recommendation systems
- factor analysis
- product recommendation
- intrusion detection system
- tensor factorization
- user generated
- user interests
- data points
- active learning