Research on moving-object data analysis has been recently fostered by the widespread diffusion of new techniques and systems for monitoring, collecting and storing location aware data, generated by a wealth of technological infrastructures, such as GPS positioning and wireless networks. These have made available massive repositories of spatio-temporal data recording human mobile activities, that call for suitable analytical methods, capable of enabling the development of innovative, location-aware applications.
Exploring real mobility data with M-atlas / Trasarti, R.; Rinzivillo, S.; Pinelli, F.; Nanni, M.; Monreale, A.; Renso, C.; Pedreschi, D.; Giannotti, F.. - 6323:3(2010), pp. 624-627. ( European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2010 Barcelona, esp 2010) [10.1007/978-3-642-15939-8_48].
Exploring real mobility data with M-atlas
Rinzivillo S.;Pinelli F.;Nanni M.;Renso C.;
2010
Abstract
Research on moving-object data analysis has been recently fostered by the widespread diffusion of new techniques and systems for monitoring, collecting and storing location aware data, generated by a wealth of technological infrastructures, such as GPS positioning and wireless networks. These have made available massive repositories of spatio-temporal data recording human mobile activities, that call for suitable analytical methods, capable of enabling the development of innovative, location-aware applications.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
