iDoctor: Personalized and professionalized medical recommendations based on hybrid matrix factorization.
Yin ZhangMin ChenDijiang HuangDi WuYong LiPublished in: Future Gener. Comput. Syst. (2017)
Keyphrases
- matrix factorization
- recommender systems
- personalized recommendation
- collaborative filtering
- item recommendation
- cold start problem
- user profiles
- low rank
- latent factor models
- data sparsity
- factor analysis
- missing data
- negative matrix factorization
- nonnegative matrix factorization
- factorization methods
- cold start
- recommendation systems
- user interests
- clustering algorithm
- stochastic gradient descent
- variational bayesian
- personalized ranking
- tensor factorization
- user preferences
- latent factors
- user feedback