Abstract
Human mobility analysis is emerging as a more and more fundamental task to deeply understand human behavior. In the last decade these kind of studies have become feasible thanks to the massive increase in availability of mobility data. A crucial point, for many mobility applications and analysis, is to extract interesting locations for people. In this paper, we propose a novel methodology to retrieve efficiently significant places of interest from movement data. Using car drivers’ systematic movements we mine everyday interesting locations, that is, places around which people life gravitates. The outcomes show the empirical evidence that these places capture nearly the whole mobility even though generated only from systematic movements abstractions.
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Acknowledgements
This work has been partially supported by the European Commission under the FET-Open Project n. FP7-ICT-284715, ICON, and by the European Commission under the SMARTCITIES Project n. FP7-ICT-609042, PETRA.
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Guidotti, R., Monreale, A., Rinzivillo, S., Pedreschi, D., Giannotti, F. (2015). Retrieving Points of Interest from Human Systematic Movements. In: Canal, C., Idani, A. (eds) Software Engineering and Formal Methods. SEFM 2014. Lecture Notes in Computer Science(), vol 8938. Springer, Cham. https://doi.org/10.1007/978-3-319-15201-1_19
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DOI: https://doi.org/10.1007/978-3-319-15201-1_19
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