Representation method for a set of documents from the viewpoint of Bayesian statistics
Masayuki Goto, T. Ishida, Shigeichi Hirasawa · 2004
In this paper, we consider the Bayesian approach for representation of a set of documents. In the field of representation of a set of documents, many previous models, such as the latent semantic analysis (LSA), the probabilistic latent semantic analysis (PLSA), the semantic aggregate model (SAM), the Bayesian latent semantic analysis (BLSA), and so on, were proposed. In this paper, we formulate the Bayes optimal solutions for estimation of parameters and selection of the dimension of the hidden latent class in these models and analyze it's asymptotic properties.