Research on learning resource recommendation based on collaborative filtering algorithm

Yuncheng Li

doi:10.1117/12.3031248

19 July 2024 Research on learning resource recommendation based on collaborative filtering algorithm

Yuncheng Li

Proceedings Volume 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024); 131816E (2024) https://doi.org/10.1117/12.3031248
Event: Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 2024, Beijing, China

Abstract

In the internet learning environment, the diversity of online learning platforms and the complexity of learning content make it difficult for learners to efficiently select suitable learning resources. Collaborative filtering algorithm, as a widely used recommendation technology, can effectively solve this problem. This article adopts a project-based collaborative filtering algorithm, using the Slope one algorithm to reduce data sparsity. By calculating the similarity between resources, a resource similarity matrix is constructed, and then weighted average is used for prediction scoring to recommend personalized learning resources for users.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yuncheng Li "Research on learning resource recommendation based on collaborative filtering algorithm", Proc. SPIE 13181, Third International Conference on Electronic Information Engineering, Big Data, and Computer Technology (EIBDCT 2024), 131816E (19 July 2024); https://doi.org/10.1117/12.3031248

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