Planning sightseeing tours using crowdsensed trajectories

We present an application where semantically enriched trajectories obtained from crowdsensed data are used to build an advanced system for planning personalized sightseeing tours, called TRIPBUILDER. The interesting feature of TRIPBUILDER is that it uses Wikipedia content and trajectories of previous tourists collected by georeferenced Flickr photos in a complex spatio-temporal framework. The objective is to address, in an unsupervised way, the problem of suggesting a budgeted sightseeing tour based on the preferences of the tourist and the time available for the visit. We present few highlights of how TRIPBUILDER works along with a research agenda where we discuss the role of semantically enriched trajectories and crowdsourced location data in planning itineraries.