Belief Propagation Algorithm for HDP

The hierarchical Dirichlet process (HDP) model is an extension of the latent Dirichlet allocation(LDA)on the aspect of non-parametric in order to solve the problem of setting number of the topics. Belief propagation algorithm is an algorithm based on the factor graph model to inference the Bayesian posterior probability. In our paper, we propose to apply the belief propagation algorithm on the HDP model, and prove the convergence of the algorithm from the view of expectation maximization algorithm. Comparing with other algorithms, the belief propagation algorithm based on HDP is better than others in accuracy measured by perplexity