RLCF: A collaborative filtering approach based on reinforcement learning with sequential ratings.
Jung-Kyu LeeByonghwa OhJihoon YangUnsang ParkPublished in: Intell. Autom. Soft Comput. (2017)
Keyphrases
- collaborative filtering
- reinforcement learning
- recommender systems
- transfer learning
- matrix factorization
- netflix prize
- function approximation
- user ratings
- personalized recommendation
- collaborative filtering algorithms
- pearson correlation coefficient
- recommendation systems
- probabilistic matrix factorization
- model free
- user preferences
- latent factor models
- learning algorithm
- reinforcement learning algorithms
- user interests
- state space
- temporal difference
- cold start problem
- product recommendation
- user profiles
- making recommendations
- deal with information overload
- rating matrix
- machine learning
- dynamic programming
- policy search
- data sparsity
- optimal control
- recommendation algorithms
- robotic control
- optimal policy
- implicit feedback