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This paper studies the use of Latent Semantic Analysis (LSA) for automatic clustering of Czech news articles. We show that LSA is capable of yielding good results in this task as it allows us to reduce the problem of synonymy. This is a very important factor particularly for Czech, which belongs to a group of highly inflective and morphologicallyrich languages. The experimental evaluation of our clustering...
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