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Latent Semantic Variable Models
This video was recorded at Workshop on Subspace, Latent Structure and Feature Selection Techniques: Statistical and Optimisation Perspectives, Bohinj 2005. In the context of information retrieval and natural language processing, latent variable models are quite useful in modeling and discovering hidden structure that often leads to "semantic" data representations. This talk will provide an overview of the most popular approaches and discuss the range of possible applications for such models, including language modeling, ad hoc retrieval, text categorization and collaborative filtering.
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This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States
