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Content-based recommender/filtering systems help to appropriately distribute information among the individuals or organizations that could consider it of interest. In this paper we describe a filtering system to deal with the problem of assigning documents to members of the parliament potentially interested on them. The proposed approach exploits subjects taken from a conceptual thesaurus to create...
News recommendation is a very active research field. The number of online journals has increased in recent years owing to the increasing popularity of the Internet. In this context, it is important to offer user tools that facilitate faster and more accurate access to articles of interest in digital newspapers. We present two probabilistic models based on latent variables that recommend relevant news...
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