摘 要: 电子学习系统的快速发展为学习者在线学习提供了巨大的机会。然而,在线学习系统中太多的学习活动使 个体学习者很难找到合适自己的学习活动,所以在线学习系统必须有能够提供个性化产品的推荐系统。本研究首先提出 了一种模糊树状结构学习活动模型,然后结合基于知识和协同过滤推荐算法的优点提出了基于混合学习活动推荐方法的 模糊树匹配方法。 |
关键词: 电子学习;模糊集;推荐系统;树匹配 |
中图分类号: TP3-0
文献标识码: A
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基金项目: 本文系天津市大学生创新创业训练计划项目“个性化推荐算法在微课学习系统中的应用研究”(项目编号:201610069094)和天津市企业科技特派员项目“提高总体多 样性的个性化推荐系统及应用研究”(项目编号:17JCTPJC55100)研究成果之一. |
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A Fuzzy Tree Matching-Based Personalized E-Learning Recommender System |
JIANG Shuhao,JIN Ge
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( Dept.of Information Technology, Tianjin University of Commerce, Tianjin 300400, China)
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Abstract: The rapid development of e-learning systems provides learners with vast opportunities to access online learning.However,too many learning activities are emerging in an e-learning system,making it difficult for individual learners to select proper activities,thus it is necessary for such recommender systems as to provide personalized recommendations from products in the e-learning system.This paper first proposes a fuzzy tree-structured learning activity model,a fuzzy tree matching-based hybrid learning activity recommendation approach is then developed,which takes advantage of both the knowledge-based and collaborative filtering-based recommendation approaches. |
Keywords: E-learning;fuzzy set;recommender systems;tree matching |