Colaboración en el Campus.-

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As introduced in Section 3.1, another way to exploit item aspect sentiment information for recommendation is to consider the topic distribution vectors extracted from the

Since 2011, it is also the data provider of the THE World University Rankings that today analyze more than 2,000 universities using 13 carefully calibrated performance

The content, reflecting various aspects of interpretation of the historical content, in particular, the content dedicated to the October Socialistic Revolution 1917, is analyzed

• A collection of effective contact recommendation algorithms based on information retrieval (IR) tech- niques. We differentiate three groups of methods: a) direct adaptations of

A great fraction of the new links between pairs of users in social networks like Twitter, LinkedIn or Facebook are created through personalized contact

We present and evaluate various content-based recommendation models that make use of user and item profiles defined in terms of weighted lists of social tags.. The studied

pre-filtering, which prune the available user preference data according to the target recommendation context, prior to applying a recommendation algorithm; those based on contextual