Understanding human mobility with big data
Giannotti F., Gabrielli L., Pedreschi D., Rinzivillo S.
big data analytics Mobility data mining
The paper illustrates basic methods of mobility data mining, designed to extract from the big mobility data the patterns of collective movement behavior, i.e., discover the subgroups of travelers characterized by a common purpose, profiles of individual movement activity, i.e., characterize the routine mobility of each traveler. We illustrate a number of concrete case studies where mobility data mining is put at work to create powerful analytical services for policy makers, businesses, public administrations, and individual citizens.
Source: Solving Large Scale Learning Tasks. Challenges and Algorithms. Essays Dedicated to Katharina Morik on the Occasion of Her 60th Birthday, edited by Stefan Michaelis, Nico Piatkowski, Marco Stolpe, pp. 208–220, 2016
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@inbook{oai:it.cnr:prodotti:424165,
title = {Understanding human mobility with big data},
author = {Giannotti F. and Gabrielli L. and Pedreschi D. and Rinzivillo S.},
doi = {10.1007/978-3-319-41706-6_10},
booktitle = {Solving Large Scale Learning Tasks. Challenges and Algorithms. Essays Dedicated to Katharina Morik on the Occasion of Her 60th Birthday, edited by Stefan Michaelis, Nico Piatkowski, Marco Stolpe, pp. 208–220, 2016},
year = {2016}
}
0000-0003-1208-8321