Clustering of Web learners based on rough set |
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Authors: | Liu?Shuai-dong Email author" target="_blank">Chen?Shi-hongEmail author |
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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 |
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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. |
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Keywords: | rough set attributes reduction k -means clustering individualized teaching |
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