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A Latent Dirichlet Allocation/N-Gram Composite Language Model, Raymond Daniel Kulhanek

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I present a composite language model in which an n-gram language model is integrated with the Latent Dirichlet Allocation topic clustering model. I also describe a parallel architecture that allows this model to be trained over large corpora and present experimental results that show how the composite model compares to a standard n-gram model over corpora of varying size.