A novel approach to clustering access patterns in e-learning environment
Jianwen Zhao, Shen-Ming Gu, Ling He · 2010
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.