Mobility path information of cellphone users play a crucial
role in a wide range of cellphone applications, including
context-based search and advertising, early warning
systems, city-wide sensing applications such as air pollution
exposure estimation and traffic planning. However,
there is a disconnect between the low level location data
logs available from the cellphones and the high level mobility
path information required to support these cellphone
applications. In this paper, we present formal definitions to
capture the cellphone users’ mobility patterns and profiles,
and provide a complete framework, Mobility Profiler, for
discovering mobile user profiles starting from cell based location
log data. We use real-world cellphone log data (of
over 350K hours of coverage) to demonstrate our framework
and perform experiments for discovering frequent mobility
patterns and profiles. Our analysis of mobility profiles
of cellphone users expose a significant long tail in a user’s
location-time distribution: A total of 15% of a user’s time
is spent on average in locations that each appear with less
than 1% of time.
Von Murat Ali Bayir, Murat Demirbas, Nathan Eagle im Text Discovering SpatioTemporal Mobility Profiles of Cellphone Users (2009)