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This work explores the possibility of using relevant data from users’
social network to alleviate the cold-user problems in a recommender
system domain. The proposed solution extracts the most valuable
node in the graph generated by check in a venue with an Android
application using the Foursquare API. By obtaining the recommendations to this node we estimate the probability of some categories
to be similar to users tastes...