Inspired by this intuition and the block assignment we obtain in the previous section, we want to extract some prior knowledge from these blocks.
we propose an LDA with block priors, hence BP-LDA, as shown in Figure 4, which has the following generative process: Unlike conventional LDA, which uses an uninformative topic prior, BP-LDA puts a Dirichlet prior π on each block to capture the block's topic distribution and use it as an informative prior when drawing each document's topic distribution.