Neural Matrix Factorization Recommendation for User Preference Prediction Based on Explicit and Implicit Feedback.
Huazhen LiuWei WangYihan ZhangRenqian GuYaqi HaoPublished in: Comput. Intell. Neurosci. (2022)
Keyphrases
- matrix factorization
- implicit feedback
- user preferences
- collaborative filtering
- recommender systems
- explicit feedback
- user behavior
- personalized ranking
- cold start
- item recommendation
- recommendation systems
- user feedback
- factor analysis
- personalized recommendation
- prediction accuracy
- data sparsity
- user profiles
- nonnegative matrix factorization
- negative matrix factorization
- recommendation algorithms
- cold start problem
- latent factors
- information overload
- tensor factorization
- latent factor models
- learning to rank
- user ratings
- missing data
- supervised learning