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A Novel Approach to Clustering Access Patterns in E-learning Environment

机译:电子学习环境中访问模式聚类的一种新方法

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In recent years, web-based education has been growing rapidly in size and complexity. Therefore, the approaches to teaching and learning have been changing with emerging technologies over the recent past. In an e-learning environment, students' access pattern mining is an emerging technique that can be utilized to not only reveal student access interest but also improve web page recommendation. With the thoughts of fuzzy sets, this paper presents a novel approach to clustering student access patterns based on transitive closure. An algorithm is also proposed with an illustrative example.
机译:近年来,基于网络的教育的规模和复杂性一直在迅速增长。因此,在最近的几年中,随着新兴技术的出现,教学方法已经发生了变化。在电子学习环境中,学生访问模式挖掘是一种新兴技术,不仅可以用来显示学生访问兴趣,而且可以改善网页推荐。借助模糊集的思想,本文提出了一种基于传递闭包的学生访问模式聚类的新方法。还提出了具有说明性示例的算法。

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