Research on personalized recommendation system on Item-based collaborative filtering algorithm

DOI

10.2991/ameii-15.2015.61How to use a DOI?

Keywords

Distance Learning; Item based collaborative filtering algorithm; Personalized Learning

Abstract

A lot of learning resources and information occupy rural distance education platform, and farmers don't know how to find useful information in the learning platform. Personalized distance learning system can provide farmers with required learning resources. The paper analyzes classical collaborative filtering algorithms, and Item based collaborative filtering algorithm is used in distance education platform, which is experimented with the distance learning platform data. The test result show that item based collaborative filtering algorithm in prediction accuracy and coverage is better with the growing of the sparsity of the data set, and the average accuracy is82.99%, the average coverage is 99.06%.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ji-chun Zhao
AU  - Shi-hong Liu
AU  - Junfeng Zhang
PY  - 2015/04
DA  - 2015/04
TI  - Research on personalized recommendation system on Item-based collaborative filtering algorithm
BT  - Proceedings of the International Conference on Advances in Mechanical Engineering and Industrial Informatics
PB  - Atlantis Press
SP  - 338
EP  - 342
SN  - 2352-5401
UR  - https://doi.org/10.2991/ameii-15.2015.61
DO  - 10.2991/ameii-15.2015.61
ID  - Zhao2015/04
ER  -