A recommendation method for online learning resources of mathematics courses based on feature graph clustering Online publication date: Wed, 31-Jan-2024
by Zhixia Duan; Na Zhao
International Journal of Reasoning-based Intelligent Systems (IJRIS), Vol. 15, No. 3/4, 2023
Abstract: Due to the low comprehensiveness of the traditional method to the analysis of learners' needs, the degree of fitting between the recommended learning resources and the actual needs of learners is low. To solve this problem, a recommendation method for online learning resources of mathematics courses based on feature graph clustering is proposed. Construct learner feature map from cognitive level and learning preference, and analyse their attribute characteristics, behaviour characteristics and learning characteristics. Then on the basis of clustering processing, resources with the same clustering characteristics are matched as the recommendation target. The test results show that the satisfaction of the recommendation results of this method is always stable at more than 90.0%, the maximum and minimum F1-score values are 0.52 and 0.46, respectively, and it has high stability, which is obviously better than the traditional method.
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