We therefore investigate an LDA-based dimensionality-reduction approach (RLDA) to derive effective vector representations of reviews.
we model each document as a bag of words, generated from a mixture of: (a) "aspect" topics (that discuss various dimensions of the offering); (b) city-specific topics; (c) hotel-specific topics; (d) review-specific topics; 4 and (e) a background topic.