Learning Significant Locations and Predicting User Movement with GPS
ISWC '02 Proceedings of the 6th IEEE International Symposium on Wearable Computers
Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
Photo tourism: exploring photo collections in 3D
ACM SIGGRAPH 2006 Papers
World explorer: visualizing aggregate data from unstructured text in geo-referenced collections
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Towards automatic extraction of event and place semantics from flickr tags
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
IEEE Transactions on Visualization and Computer Graphics
Cellular Census: Explorations in Urban Data Collection
IEEE Pervasive Computing
Mobility detection using everyday GSM traces
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Predestination: inferring destinations from partial trajectories
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Instrumenting the city: developing methods for observing and understanding the digital cityscape
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
Automatic construction of travel itineraries using social breadcrumbs
Proceedings of the 21st ACM conference on Hypertext and hypermedia
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In recent years, the large deployment of mobile devices has led to a massive increase in the volume of records of where people have been and when they were there. The analysis of these spatio-temporal data can supply high-level human behaviour information valuable to urban planners, local authorities, and designer of location-based services. In this article, we describe our approach to collect and analyse the history of physical presence of tourists from the digital footprints they publicly disclose on the web. Our work takes place in the Province of Florence in Italy, where the insights on the visitors' flows and on the nationalities of the tourists who do not sleep in town has been limited to information from survey-based hotel and museums frequentation. In fact, most local authorities in the world must face this dearth of data on tourist dynamics. In this case study, we used a corpus of geographically referenced photos taken in the province by 4280 photographers over a period of two years. Based on the disclosure of the location of the photos, we design geovisualisations to reveal the tourist concentration and spatio-temporal flows. Our initial results provide insights on the density of tourists, the points of interests they visit as well as the most common trajectories they follow.