PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Guidotti R., Monreale A., Rinzivillo S., Pedreschi D., Giannotti F. Retrieving points of interest from human systematic movements. Carlos Canal, Akram Idani (eds.). (Lecture Notes in Computer Science, vol. 8938). Cham, Switzerland: Springer, 2015.
 
 
Abstract
(English)
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.
URL: http://link.springer.com/chapter/10.1007%2F978-3-319-15201-1_19
DOI: 10.1007/978-3-319-15201-1_19
Subject Points of Interest
Collective mobility behavior
Individual mobility profile
H.2.8 Database Applications. Data Mining
68W01


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