An Improvement of Matrix Factorization with Bound Constraints for Recommender Systems.
Kazuki MoriTung NguyenTomohiro HaradaRuck ThawonmasPublished in: IIAI-AAI (2016)
Keyphrases
- matrix factorization
- recommender systems
- collaborative filtering
- low rank
- data sparsity
- nonnegative matrix factorization
- factorization methods
- cold start problem
- data matrix
- negative matrix factorization
- variational bayesian
- factor analysis
- probabilistic matrix factorization
- item recommendation
- recommendation quality
- missing data
- user preferences
- user feedback
- implicit feedback
- user profiles
- rating prediction
- lower bound
- constraint programming
- stochastic gradient descent
- pairwise
- user interests
- personalized recommendation
- high order
- tensor factorization
- worst case
- personalized ranking