Abstract—With the development of Internet technology,
information resource is being spread widely, thus the issue of
information overload formed. It becomes more difficult for users
to retrieve their needed information from so enormous
information space. To solve the issue of information overload,
recommender system emerges as the times require. This paper
presents the personalized e-learning system based on
Collaborative Filtering Recommender Algorithm. And the
system will be implemented based on EGL with the advantages
of developers paying attention to the business issues without
caring for software technical details. By the solution of EGL, the
function of personalized information recommendation of
e-learning system will be achieved and personalized information
will be recommended to users to help them improve learning
efficiency. The results show that the solution of EGL is more
flexible and simple, reduce the development cycle and cost,
improved the real-time requirement of e-learning system.
Index Terms—EGL, recommender system, personalized, e-learning, architecture.
The authors are with Software College, Shenyang Normal University, Shenyang, Liaoning, China (corresponding author: Song Bo; e-mail: firstname.lastname@example.org, email@example.com).
Cite: Jie Gao and Bo Song, "A Personalized e-Learning System Based on EGL," International Journal of Machine Learning and Computing vol. 4, no. 5, pp. 411-416, 2014.