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Applications that allow the users to search for nearby points of interest have, recently, become very popular amongst mobile device users. However, the increasing amount of available information and the limitations of current mobile devices can hinder an efficient and helpful user experience. It is fundamental that what is shown to the user is relevant. We propose an adaptive recommendation function that uses location and temporal contexts combined with the historical context of the previous searches to quantify the relevance of the points of interest shown to the user.