Mining tourist routes using Flickr traces

Authors:
Gaël Chareyron;Jérôme Da-Rugna;Bérengère Branchet
Affiliations:
Pôle Universitaire Léonard de Vinci, Paris La Défense, France and University of Paris 1 Pantheon-Sorbonne, Paris, France;Pôle Universitaire Léonard de Vinci, Paris La Défense, France and University of Paris 1 Pantheon-Sorbonne, Paris, France;Pôle Universitaire Léonard de Vinci, Paris La Défense, France
Venue:
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Year:
2013

Citing 3
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Mining Travel Patterns from Geotagged Photos

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Abstract

This paper is about a new methodology to automatically rebuild main paths from Flickr's traces. Our geotagged image metadata's corpus allows the construction of each photographer's timeline. The tourist's itinerary in the destination can then be reconstructed considering two modes: the fastest path and the most likely path. Major paths are directly extracted from the fusion of all itineraries. To illustrate the multi-scale efficiency of this work, several fields of study are presented: Berlin, the Loire Valley and the Palace of Versailles.