This technical note is intended to review the foundations of Bayesian parameter estimation in the discrete domain, which is necessary to understand the inner workings of topic-based text analysis approaches like probabilistic latent semantic analysis (PLSA), latent Dirichlet allocation (LDA) and other mixture models of count data.

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