Survey of Reinforcement Learning Based Recommender Systems
Recommender systems are devoted to find and automatically recommend valuable information and services for users from massive data,which can effectively solve the information overload problem,and become an important information technology in the era of big data.However,the problems of data sparsity,c...
Main Author: | YU Li, DU Qi-han, YUE Bo-yan, XIANG Jun-yao, XU Guan-yu, LENG You-fang |
---|---|
Format: | Article |
Language: | zho |
Published: |
Editorial office of Computer Science
2021-10-01
|
Series: | Jisuanji kexue |
Subjects: | |
Online Access: | http://www.jsjkx.com/fileup/1002-137X/PDF/1002-137X-2021-10-1.pdf |
Similar Items
-
A Systematic Study on Reinforcement Learning Based Applications
by: Keerthana Sivamayil, et al.
Published: (2023-02-01) -
Hedging using reinforcement learning: Contextual k-armed bandit versus Q-learning
by: Loris Cannelli, et al.
Published: (2023-11-01) -
A Reinforcement-Learning-Based Distributed Resource Selection Algorithm for Massive IoT
by: Jing Ma, et al.
Published: (2019-09-01) -
Reinforcement Learning for Stock Prediction and High-Frequency Trading With T+1 Rules
by: Weipeng Zhang, et al.
Published: (2023-01-01) -
EmoWare: A Context-Aware Framework for Personalized Video Recommendation Using Affective Video Sequences
by: Abhishek Tripathi, et al.
Published: (2019-01-01)