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In the last two decades, text modeling techniques have been used for various applications, including the analysis of topics in different text documents, where the aim is to provide a document representation in terms of topic distribution. This work aims to show some results on a generalization of the popular latent Dirichlet allocation model, with a particular focus on the clustering of text documents.