Intelligent learning system based on personalized recommendation technology

Intelligent learning system based on personalized recommendation technology With the continuous development of networks, web-based e-learning is changing the way people acquire knowledge. An increasing number of learners are eager to acquire more knowledge through personalized and intelligent means. Based on content recommendation and collaborative filtering recommendation algorithm, this paper proposes a hybrid recommen- dation algorithm which can improve the efficiency of traditional recommendation algorithm. The presented research introduces the whole process of user interest model and teaching resources model, which also designs and implements the personalized network teaching resources system prototype. Finally, in comparison with the traditional recommendation algorithm, the improved hybrid recommendation algorithm has more advantages in personalized intelligent educational resources recommendation system. Keywords Smart education  Learning resource  Collaborative filtering  SVM 1 Introduction With the continuous development of the network technol- ogy, web-based e-learning [1, 2] is changing the way people acquire knowledge; more and more learners are & Haining Li eager to acquire more knowledge through more personal- 2002000051@hhit.edu.cn; lhaining@nccu.edu ized and intelligent way. In e-learning environment, with & Shu Zhang the rapid expansion of teaching resources and information, 2007000044@hhit.edu.cn the ‘‘information overload,’’ ‘‘resources lost’’ and other Hui Li problems appeared one after another. How to push out the 201100003@hhit.edu.cn; 2002000051@hhit.edu.cn http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Neural Computing and Applications Springer Journals

Intelligent learning system based on personalized recommendation technology

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Publisher
Springer Journals
Copyright
Copyright © 2018 by The Natural Computing Applications Forum
Subject
Computer Science; Artificial Intelligence (incl. Robotics); Data Mining and Knowledge Discovery; Probability and Statistics in Computer Science; Computational Science and Engineering; Image Processing and Computer Vision; Computational Biology/Bioinformatics
ISSN
0941-0643
eISSN
1433-3058
D.O.I.
10.1007/s00521-018-3510-5
Publisher site
See Article on Publisher Site

Abstract

With the continuous development of networks, web-based e-learning is changing the way people acquire knowledge. An increasing number of learners are eager to acquire more knowledge through personalized and intelligent means. Based on content recommendation and collaborative filtering recommendation algorithm, this paper proposes a hybrid recommen- dation algorithm which can improve the efficiency of traditional recommendation algorithm. The presented research introduces the whole process of user interest model and teaching resources model, which also designs and implements the personalized network teaching resources system prototype. Finally, in comparison with the traditional recommendation algorithm, the improved hybrid recommendation algorithm has more advantages in personalized intelligent educational resources recommendation system. Keywords Smart education  Learning resource  Collaborative filtering  SVM 1 Introduction With the continuous development of the network technol- ogy, web-based e-learning [1, 2] is changing the way people acquire knowledge; more and more learners are & Haining Li eager to acquire more knowledge through more personal- 2002000051@hhit.edu.cn; lhaining@nccu.edu ized and intelligent way. In e-learning environment, with & Shu Zhang the rapid expansion of teaching resources and information, 2007000044@hhit.edu.cn the ‘‘information overload,’’ ‘‘resources lost’’ and other Hui Li problems appeared one after another. How to push out the 201100003@hhit.edu.cn; 2002000051@hhit.edu.cn

Journal

Neural Computing and ApplicationsSpringer Journals

Published: Jun 6, 2018

References

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