Research on Personalized Recommendation Algorithm of Educational Resources Based on Deep Neural Network

Personalized learning is a trend in the development of higher education. We use artificial intelligence technology to realize recommendation of educational resources which becomes issue in higher education. By studying the algorithm and content and combining with deep learning technology, this paper establishes model of educational resources, and puts forward related algorithms of resource filtering from three aspects: resource filtering, recommendation and display respectively. At the same time, an online learning platform is combined with Python language to train model through data sets. The algorithm is compared with traditional algorithms such as SVM, ER and DT. The average absolute error and mean square error and effectiveness of the algorithm proposed in this paper, and further improve the efficiency of educational resource recommendation. It provides a reference of educational resources.

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Publication Details

Published
2024-09-23
DOI
https://doi.org/10.1109/icedcs64328.2024.00077
Citations
1
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
0.78
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Research on Personalized Recommendation Algorithm of Educational Resources Based on Deep Neural Network

Siyi Liu, Xiangyu Ding, Caoyuan Ma
1 citations
Recommender Systems and Techniques
0.78
article

Research on Personalized Recommendation Algorithm of Educational Resources Based on Deep Neural Network

Siyi Liu, Xiangyu Ding, Caoyuan Ma
article en
1 citations

Abstract

Personalized learning is a trend in the development of higher education. We use artificial intelligence technology to realize recommendation of educational resources which becomes issue in higher education. By studying the algorithm and content and combining with deep learning technology, this paper establishes model of educational resources, and puts forward related algorithms of resource filtering from three aspects: resource filtering, recommendation and display respectively. At the same time, an online learning platform is combined with Python language to train model through data sets. The algorithm is compared with traditional algorithms such as SVM, ER and DT. The average absolute error and mean square error and effectiveness of the algorithm proposed in this paper, and further improve the efficiency of educational resource recommendation. It provides a reference of educational resources.

Shandong University of Technology (CN)
Openalex Percentile: Top 17%
Recommender Systems and Techniques
0.78
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Research on Personalized Recommendation Algorithm of Educational Resources Based on Deep Neural Network — Siyi Liu, Xiangyu Ding, et al. · (2024) | TGRS Research Map | TGRS