Trajectories of moving objects have been an active research topic for over a decade. Classical approaches to analyze the trajectories of these objects are mainly based on large amounts of data acquired from positioning devices, such GPS receivers. GPS data has the advantage of describing the trajectory of an object with a great level of detail and high accuracy, but the data do not carry any kind of semantic information. On the other hand, nowadays it is growing the number of interactions in social networks with some kind of information about the location of the user. Georeferenced social interactions are an important source of semantic about user's trajectories and activities. This work proposes a solution for reconstructing travel histories using heterogeneous social track sources posts in social networks, GPS positioning data, location history data generated by cloud services or any digital footprint with an associated geographic position. The solution encompasses a conceptual model; a methodology to reconstruct travel histories based on heterogeneous social tracks sources; and an application to present the reconstructed travel itinerary in a graphical and interactive fashion. An experiment conducted with real travel experiences showed that the proposed solution is a reasonable way to reconstruct travels histories, geographically and semantically, in an automatic fashion.
['Amon Veiga Santana', 'Jorge Campos']
Travel History: Reconstructing Semantic Trajectories Based on Heterogeneous Social Tracks Sources