DocumentCode
2825647
Title
Notice of Retraction
A Recommender System Based on Web Data Mining for Personalized E-Learning
Author
Jinhua Sun ; Yanqi Xie
Author_Institution
Dept. of Comput. Sci. & Technol., Xiamen Univ. of Technol., Xiamen, China
fYear
2009
fDate
19-20 Dec. 2009
Firstpage
1
Lastpage
4
Abstract
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper, we introduce a Web data mining solution to e-learning system to discover hidden patterns strategies from their learners and Web data, describe a personalized recommender system that uses web mining techniques for recommending a student which (next) links to visit within an adaptable e-learning system, propose a new framework based on data mining technology for building a Web-page recommender system, and demonstrate how data mining technology can be effectively applied in an e-learning environment.
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
In this paper, we introduce a Web data mining solution to e-learning system to discover hidden patterns strategies from their learners and Web data, describe a personalized recommender system that uses web mining techniques for recommending a student which (next) links to visit within an adaptable e-learning system, propose a new framework based on data mining technology for building a Web-page recommender system, and demonstrate how data mining technology can be effectively applied in an e-learning environment.
Keywords
Internet; computer aided instruction; data mining; recommender systems; Web data mining; Web-page recommender system; personalized e-learning; Association rules; Computer science; Data mining; Electronic learning; Information analysis; Management training; Recommender systems; Sun; Web mining; Web server;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-4994-1
Type
conf
DOI
10.1109/ICIECS.2009.5363838
Filename
5363838
Link To Document