I agree with the previous postings about the overly complicated language and words used in the paper. However I found that the paper was well designed and achieved to show its well-defined goal (the superiority of PLSA method over several existing methods, which can be mainly contributed to the solid statistical foundations that PLSA is based on).

Even though the ability of tempered EM to avoid over-fitting was really appealing, I somehow felt that the control parameter Beta unnecessarily increased complexity. I would have really liked to see an entry in the table, which compared the different variants, for a version that used standard EM for the maximization of the "predictive power of the model."

I really liked figure 2, which nicely demonstrated the dynamics of the model, showing both the posterior and mixture probabilities for a sample query.

Finally, although not all the variants of PLSA are crystal clear to me, but the results reported suggest that the method presented is clearly superior both in terms of precision and recall.