DocumentCode
2927675
Title
Based on the Reinforcement Learning Association Rules Recommendation Study
Author
Wang, Jinqiao ; Yang, Qing ; Zhu, Li ; Sun, Junli
Author_Institution
Dept. of Comput. Sci., Huazhong Normal Univ., Wuhan, China
fYear
2009
fDate
12-14 Oct. 2009
Firstpage
392
Lastpage
395
Abstract
Reinforcement learning is an important method of machine learning. This paper using the graph theory to express varieties of knowledge points, which their´s relationship is expressed by the graph of topological graph. Applied the Technology of association rule Recommendation to deal with the relationship between these knowledge points, give the corresponding of the recommendation work flow chart. In the paper data tables used to store the knowledge points, the algorithm to demonstrate the technical of association rule Recommendation feasibility and rationality.
Keywords
data mining; graph theory; learning (artificial intelligence); association rules; graph theory; machine learning; reinforcement learning; topological graph; Association rules; Computer science; Data mining; Flowcharts; Graph theory; Intelligent robots; Machine learning; Resonance light scattering; Signal generators; Testing; Recommendation Systems data mining; association rules; reinforcement learning; topological graph;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantics, Knowledge and Grid, 2009. SKG 2009. Fifth International Conference on
Conference_Location
Zhuhai
Print_ISBN
978-0-7695-3810-5
Type
conf
DOI
10.1109/SKG.2009.19
Filename
5370016
Link To Document