In this paper we propose TripBuilder, a new framework for personalized touristic tour planning. We mine from Flickr the information about the actual itineraries followed by a multitude of different tourists, and we match these itinera- ries on the touristic Point of Interests available from Wikipedia. The task of planning personalized touristic tours is then modeled as an instance of the Generalized Maximum Cover- age problem. Wisdom-of-the-crowds information allows us to derive touristic plans that maximize a measure of inter- est for the tourist given her preferences and visiting time- budget. Experimental results on three different touristic cities show that our approach is effective and outperforms strong baselines.