Data di Pubblicazione:
2016
Abstract:
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.
Tipologia CRIS:
02.01 Contributo in volume (Capitolo o Saggio)
Keywords:
Mobility data mining; big data analytics
Elenco autori:
Gabrielli, Lorenzo; Giannotti, Fosca; Rinzivillo, Salvatore
Link alla scheda completa:
Titolo del libro:
Solving Large Scale Learning Tasks. Challenges and Algorithms. Essays Dedicated to Katharina Morik on the Occasion of Her 60th Birthday