Title: Personalised recommendation of educational resources based on collaborative filtering

Authors: Yi Song

Addresses: Academic Affairs Office, Changsha Social Work College, Changsha, 410004, China

Abstract: In order to overcome the problems of low accuracy and long processing time of personalised recommendation of educational resources in traditional personalised recommendation methods of educational resources, a personalised recommendation method of educational resources based on collaborative filtering is proposed. First, the membership relationship between knowledge points and educational resources are calculated. Then educational resources are modelled with the help of fuzzy set theory, a learner model is created by using four models, a learner interest matrix is established, and learner characteristics are extracted. Finally, learner similarity based on learner collaborative filtering recommendation algorithm is calculated, and the latest learner set is selected. The score of the nearest neighbour learner on the item is used to predict the score of the target learner, so as to generate recommendation results. The simulation results show that the proposed method has higher accuracy and shorter recommendation time for personalised recommendation of educational resources.

Keywords: collaborative filtering; educational resources; interest matrix; personalised recommendation; similarity.

DOI: 10.1504/IJBIDM.2024.137737

International Journal of Business Intelligence and Data Mining, 2024 Vol.24 No.3/4, pp.309 - 323

Received: 18 Nov 2022
Accepted: 07 Mar 2023
Published online: 04 Apr 2024 *

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