Mobility profiler: A framework for discovering mobility profiles of cell phone users

Abstract

Mobility path information of cell phone users play a crucial role in a wide range of cell phone 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 cell phones and the high level mobility path information required to support these cell phone applications. In this paper, we present formal definitions to capture the cell phone users’ mobility patterns and profiles, and provide a complete framework, Mobility Profiler, for discovering mobile cell phone user profiles starting from cell based location data. We use real-world cell phone log data (of over 350 K h of coverage) to demonstrate our framework and perform experiments for discovering frequent mobility patterns and profiles. Our analysis of mobility profiles of cell phone users expose a significant long tail in a user’s location-time distribution: A total of 15% of a cell phone user’s time is spent on average in locations that each appears with less than 1% of total time.