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Journal of Electrical and Computer Engineering
Volume 2017 (2017), Article ID 9720396, 7 pages
Research Article

Online Behavior Analysis-Based Student Profile for Intelligent E-Learning

1College of Computer Science and Information Engineering, Tianjin University of Science & Technology, Tianjin 300222, China
2China GRIDCOM Co., Ltd., Shenzhen 518031, China
3Xiamen Great Power Geo Information Technology Co. Ltd., Xiamen, Fujian 361000, China

Correspondence should be addressed to Yiying Zhang; nc.ude.tsut@gnahzgniyiy

Received 15 November 2016; Accepted 23 February 2017; Published 13 March 2017

Academic Editor: Sook Yoon

Copyright © 2017 Kun Liang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


With the development of mobile platform, such as smart cellphone and pad, the E-Learning model has been rapidly developed. However, due to the low completion rate for E-Learning platform, it is very necessary to analyze the behavior characteristics of online learners to intelligently adjust online education strategy and enhance the quality of learning. In this paper, we analyzed the relation indicators of E-Learning to build the student profile and gave countermeasures. Adopting the similarity computation and Jaccard coefficient algorithm, we designed a system model to clean and dig into the educational data and also the students’ learning attitude and the duration of learning behavior to establish student profile. According to the E-Learning resources and learner behaviors, we also present the intelligent guide model to guide both E-Learning platform and learners to improve learning things. The study on student profile can help the E-Learning platform to meet and guide the students’ learning behavior deeply and also to provide personalized learning situation and promote the optimization of the E-Learning.