This thesis applies Latent Dirichlet Allocation (LDA) to the problem of topic and topic change in conversational threads using e-mail. We demonstrate that LDA can be used to successfully classify raw e-mail messages with threads to which they belong, and compare the results with those for processed threads, where quoted and reply text have been removed. Raw thread classification performs better, but processed threads show promise. We then present two ...
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