Recommendations Based on Comprehensively Exploiting the Latent Factors Hidden in Items' Ratings and Content.
Shanshan FengJian CaoJie WangShiyou QianPublished in: ACM Trans. Knowl. Discov. Data (2017)
Keyphrases
- latent factors
- latent factor models
- matrix factorization
- factor analysis
- recommender systems
- implicit feedback
- collaborative filtering
- latent variables
- topic models
- nonnegative matrix factorization
- user preferences
- probabilistic latent semantic analysis
- personalized recommendation
- latent dirichlet allocation
- user feedback
- eye tracking
- probabilistic model
- recommendation systems
- user interests
- user interaction