Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)

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Collaborative Filtering of Learning Resources Recommendation Based on Learners’ Viewing Behavior

Authors
Chong Wang1, Ziyao Wang1, *, Yongzhe Zhao1, Yixuan Zhao2
1School of Business, Guilin University of Electronic Technology, Guilin, 450305, China
2School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, 450305, China
*Corresponding author. Email: wjyo2691@163.com
Corresponding Author
Ziyao Wang
Available Online 12 December 2022.
DOI
10.2991/978-94-6463-024-4_78How to use a DOI?
Keywords
viewing behavior; learning resources; collaborative filtering; personalized recommendation
Abstract

With the popularity of online education and the development of information technology, the number of learning resources on the Internet has increased geometrically, making it often impossible for learners to obtain more accurate learning resource recommendations. The main form of online learning for learners is watching online video courses, making good use of learners’ behavioral data can improve the accuracy of recommended resources for them. For this purpose, this research proposes a collaborative filtering learning resource recommendation method based on learners’ viewing behavior; Firstly, the learning resource attributes and learners’ viewing behavior are mined to build their interest preference model. Secondly, the model is incorporated into the collaborative filtering recommendation algorithm using an improved Pearson similarity calculation method; Finally, the personalized recommendation of learning resources is completed. The experimental results show that the method improves the accuracy and recall rate of personalized learning resource recommendations to a certain extent compared to the traditional collaborative filtering recommendation algorithm.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
12 December 2022
ISBN
978-94-6463-024-4
ISSN
2589-4900
DOI
10.2991/978-94-6463-024-4_78How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Chong Wang
AU  - Ziyao Wang
AU  - Yongzhe Zhao
AU  - Yixuan Zhao
PY  - 2022
DA  - 2022/12/12
TI  - Collaborative Filtering of Learning Resources Recommendation Based on Learners’ Viewing Behavior
BT  - Proceedings of the 2022 2nd International Conference on Education, Information Management and Service Science (EIMSS 2022)
PB  - Atlantis Press
SP  - 743
EP  - 754
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-024-4_78
DO  - 10.2991/978-94-6463-024-4_78
ID  - Wang2022
ER  -