Incremental learning for matrix factorization in recommender systems.
Tong YuOle J. MengshoelAlvin JudeEugen FellerJulien ForgeatNimish RadiaPublished in: IEEE BigData (2016)
Keyphrases
- incremental learning
- matrix factorization
- recommender systems
- collaborative filtering
- low rank
- incremental learning algorithm
- nonnegative matrix factorization
- negative matrix factorization
- cold start problem
- data sparsity
- semi supervised
- stochastic gradient descent
- factor analysis
- implicit feedback
- factorization methods
- learning process
- user preferences
- user profiles
- fuzzy artmap
- tensor factorization
- supervised learning
- recommendation quality
- probabilistic matrix factorization
- latent factors
- latent factor models
- item recommendation
- labeled data
- rating prediction