Exploring Clustering-Based Reinforcement Learning for Personalized Book Recommendation in Digital Library.
Xinhua WangYuchen WangLei GuoLiancheng XuBaozhong GaoFangai LiuWei LiPublished in: Inf. (2021)
Keyphrases
- digital libraries
- reinforcement learning
- personalized recommendation
- book presents
- book covers
- user modeling
- personalized information
- information filtering
- collaborative filtering
- function approximation
- recommender systems
- personalized services
- product recommendation
- personal preferences
- user profiles
- recommendation systems
- web personalization
- cutting edge
- cultural heritage
- researchers and practitioners
- news recommendation
- digital library systems
- markov decision processes
- author biography
- user profiling
- metadata
- multi agent
- information resources
- digital documents
- individual user
- e learning
- comprehensive guide
- reinforcement learning algorithms
- graduate students
- database applications
- topics covered include
- optimal control
- bibliographic information
- sci tech
- databases
- user specific
- web users
- user model
- transfer learning
- optimal policy
- state space
- dynamic programming
- social networks
- machine learning