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Clustering Student Discussion Messages on Online Forumby Visualization and Non-Negative Matrix Factorization
School of Computing and Mathematics, Charles Sturt University, Australia
Faculty of Education Information Technology, South China Normal University, China
School of Computing and Mathematics, Charles Sturt University, Australia
Faculty of Information and Communication Technologies Swinburne University of Technology, Australia
- 1 School of Computing and Mathematics, Charles Sturt University, Australia
- 2 Faculty of Education Information Technology, South China Normal University, China
- 3 School of Computing and Mathematics, Charles Sturt University, Australia
- 4 Faculty of Information and Communication Technologies Swinburne University of Technology, Australia
Journal of Software Engineering and Applications·Volume 06 (2013)·Pages 7–12·Published 22 July 2013·DOI10.4236/jsea.2013.67B002
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Abstract
The use of online discussion forum can effectively engage students in their studies. As the number of messages posted on the forum is increasing, it is more difficult for instructors to read and respond to them in a prompt way. In this paper, we apply non-negative matrix factorization and visualization to clustering message data, in order to provide a summary view of messages that disclose their deep semantic relationships. In particular, the NMF is able to find the underlying issues hidden in the messages about which most of the students are concerned. Visualization is employed to estimate the initial number of clusters, showing the relation communities. The experiments and comparison on a real dataset have been reported to demonstrate the effectiveness of the approaches.
KeywordsOnline ForumClusterNon-Negative Matrix FactorizationVisualization
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