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Discovering the geographical borders of human mobility

Articolo
Data di Pubblicazione:
2012
Abstract:
The availability of massive network and mobility data from diverse domains has fostered the analysis of human behavior and interactions. Broad, extensive, and multidisciplinary research has been devoted to the extraction of non-trivial knowledge from this novel form of data. We propose a general method to determine the influence of social and mobility behavior over a specific geographical area in order to evaluate to what extent the current administrative borders represent the real basin of human movement. We build a network representation of human movement starting with vehicle GPS tracks and extract relevant clusters, which are then mapped back onto the territory, finding a good match with the existing administrative borders. The novelty of our approach is the focus on a detailed spatial resolution, we map emerging borders in terms of individual municipalities, rather than macro regional or national areas. We present a series of experiments to illustrate and evaluate the effectiveness of our approach.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Community discovery; Mobility data mining
Elenco autori:
Pedreschi, Dino; Coscia, Michele; Pezzoni, Fabio; Mainardi, Simone; Giannotti, Fosca; Rinzivillo, Salvatore
Autori di Ateneo:
RINZIVILLO SALVATORE
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/4691
Pubblicato in:
KI - KÜNSTLICHE INTELLIGENZ
Journal
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URL

http://link.springer.com/article/10.1007%2Fs13218-012-0181-8
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