A personalised matching method of English learning data packages based on knowledge map

In order to improve the retention rate of learning data and the coverage rate of matching results, this paper designs a personalised matching method of English learning data packages based on knowledge map. First, cluster the learning packages information and analyse user interest. Secondly, the knowledge map network is established and the sequence nodes are analysed. Then, the user features and data packages features are decomposed from the relational entities of the knowledge map to obtain independent user features and data packages features; Finally, users' interests and preferences are optimised by updating the node weights in the knowledge map, and personalised matching is realised according to the similarity between data packets. Experiment shows that this method can control the retention rate of the learning date packages at more than 90% and the matching coverage at more than 95%, which shows that this method can meet the needs of users.

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Publication Details

Journal
International Journal of Reasoning-based Intelligent Systems
Published
2025-01-01
DOI
https://doi.org/10.1504/ijris.2025.146927
Primary Topic
Educational Technology and Assessment
Type
article
Field-Weighted Citation Impact
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article

A personalised matching method of English learning data packages based on knowledge map

Wei Liu
International Journal of Reasoning-based Intelligent Systems
Educational Technology and Assessment
article

A personalised matching method of English learning data packages based on knowledge map

Wei Liu
article en

Abstract

In order to improve the retention rate of learning data and the coverage rate of matching results, this paper designs a personalised matching method of English learning data packages based on knowledge map. First, cluster the learning packages information and analyse user interest. Secondly, the knowledge map network is established and the sequence nodes are analysed. Then, the user features and data packages features are decomposed from the relational entities of the knowledge map to obtain independent user features and data packages features; Finally, users' interests and preferences are optimised by updating the node weights in the knowledge map, and personalised matching is realised according to the similarity between data packets. Experiment shows that this method can control the retention rate of the learning date packages at more than 90% and the matching coverage at more than 95%, which shows that this method can meet the needs of users.

International Journal of Reasoning-based Intelligent SystemsVol. 17(2)
Dalian Jiaotong University (CN)
Quality Education
Openalex Percentile: Top 78%
Educational Technology and Assessment
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A personalised matching method of English learning data packages based on knowledge map — Wei Liu · International Journal of Reasoning-based Intelligent Systems (2025) | TGRS Research Map | TGRS