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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.