Accordingly, we propose a dimensionality-reduction approach, based on Latent Dirichlet Allocation (LDA) (Blei et al, 2003), to obtain a vector representation of reviews for the ranking algorithm that generalizes across reviews of different offerings.
we train an LDA-based topic model to view each review as a mixture of aspect-, city-, hotel-and review-specific topics (see Section 6).