Exploiting user and item embedding in latent factor models for recommendations.
Zhaoqiang LiJiajin HuangNing ZhongPublished in: WI (2017)
Keyphrases
- latent factor models
- recommender systems
- collaborative filtering
- user preferences
- personalized recommender systems
- matrix factorization
- item recommendation
- user ratings
- making recommendations
- latent factors
- cold start problem
- active user
- recommendation systems
- user feedback
- recommendation algorithms
- topic models
- user interface
- implicit feedback
- personalized recommendation
- information overload
- user interests
- cold start
- vector space
- user similarity
- user interaction
- user profiles
- eye tracking
- user behavior