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Clustering of Web learners based on rough set
Authors:Liu?Shuai-dong  Email author" target="_blank">Chen?Shi-hongEmail author
Institution:(1) School of Computer, Wuhan University, 430072 Wuhan, Hubei, China;(2) National Engineering Research Center for Multimedia Software, Wuhan University, 430072 Wuhan, Hubei, China
Abstract:The demand for individualized teaching from E-learning websites is rapidly increasing due to the huge differences existed among Web learners. A method for clustering Web learners based on rough set is proposed. The basic idea of the method is to reduce the learning attributes prior to clustering, and therefore the clustering of Web learners is carried out in a relative low-dimensional space. Using this method, the E-learning websites can arrange corresponding teaching content for different clusters of learners so that the learners’ individual requirements can be more satisfied. Foundation item: Supported by the National “863” Program of China (2002AA111010, 2003AA001032) Biography: LIU Shuai-dong (1979-), male, Master candidate, research direction: knowledge discovery and individualized learning techniques.
Keywords:rough set  attributes reduction  k -means clustering  individualized teaching
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