Predicting Missing Ratings in Recommender Systems: Adapted Factorization Approach.
Carme JuliàAngel Domingo SappaFelipe LumbrerasJoan SerratAntonio M. LópezPublished in: Int. J. Electron. Commer. (2009)
Keyphrases
- recommender systems
- collaborative filtering
- matrix factorization
- cold start problem
- netflix prize
- user preferences
- cold start
- missing data
- user ratings
- personalized recommendation
- tensor factorization
- rating prediction
- collaborative filtering algorithms
- low rank
- recommendation algorithms
- data sparsity
- factorization methods
- active user
- latent factor models
- implicit feedback
- product recommendation
- collaborative filtering recommender systems
- rating matrix
- user model
- user profiles
- user profiling
- user modeling
- information overload
- recommendation systems
- item recommendation
- item based collaborative filtering
- factorization method
- singular value decomposition
- pairwise
- information filtering
- collaborative recommendation
- missing values
- incomplete data
- user interests
- user similarity
- personal preferences
- recommendation quality
- user feedback
- link prediction