Leveraging Kernel-Incorporated Matrix Factorization for App Recommendation.
Chenyang LiuJian CaoShanshan FengPublished in: ACM Trans. Knowl. Discov. Data (2019)
Keyphrases
- matrix factorization
- collaborative filtering
- recommender systems
- item recommendation
- data sparsity
- user ratings
- cold start problem
- latent factor models
- low rank
- recommendation systems
- cold start
- factorization methods
- kernel function
- nonnegative matrix factorization
- personalized recommendation
- user preferences
- missing data
- variational bayesian
- implicit feedback
- personalized ranking
- rating prediction
- factor analysis
- negative matrix factorization
- recommendation algorithms
- support vector
- tensor factorization
- feature space
- probabilistic matrix factorization
- latent factors
- user experience
- user interests
- link prediction
- kernel methods
- user behavior
- social networks