A User-Centered Location Model
Personal and Ubiquitous Computing
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
Learning Significant Locations and Predicting User Movement with GPS
ISWC '02 Proceedings of the 6th IEEE International Symposium on Wearable Computers
Using GPS to learn significant locations and predict movement across multiple users
Personal and Ubiquitous Computing
Route profiling: putting context to work
Proceedings of the 2004 ACM symposium on Applied computing
Social Serendipity: Mobilizing Social Software
IEEE Pervasive Computing
Reality mining: sensing complex social systems
Personal and Ubiquitous Computing
Analysis of random mobility models with PDE's
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
Proceedings of the 7th ACM international symposium on Mobile ad hoc networking and computing
MPTrain: a mobile, music and physiology-based personal trainer
Proceedings of the 8th conference on Human-computer interaction with mobile devices and services
The CarTel mobile sensor computing system
Proceedings of the 4th international conference on Embedded networked sensor systems
Building a sensor network of mobile phones
Proceedings of the 6th international conference on Information processing in sensor networks
Learning and inferring transportation routines
Artificial Intelligence
Proceedings of the 1st ACM SIGMOBILE international workshop on Systems and networking support for healthcare and assisted living environments
IEEE Pervasive Computing
Impact of Human Mobility on Opportunistic Forwarding Algorithms
IEEE Transactions on Mobile Computing
Mobile user movement prediction using bayesian learning for neural networks
IWCMC '07 Proceedings of the 2007 international conference on Wireless communications and mobile computing
The diameter of opportunistic mobile networks
CoNEXT '07 Proceedings of the 2007 ACM CoNEXT conference
Experimenting with real-life opportunistic communications using windows mobile devices
CoNEXT '07 Proceedings of the 2007 ACM CoNEXT conference
Distributed community detection in delay tolerant networks
Proceedings of 2nd ACM/IEEE international workshop on Mobility in the evolving internet architecture
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Micro-Blog: sharing and querying content through mobile phones and social participation
Proceedings of the 6th international conference on Mobile systems, applications, and services
Bridging centrality: graph mining from element level to group level
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Discrete Applied Mathematics
iMAP: Indirect measurement of air pollution with cellphones
PERCOM '09 Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications
Exploiting social interactions in mobile systems
UbiComp '07 Proceedings of the 9th international conference on Ubiquitous computing
Clustering and prediction of mobile user routes from cellular data
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Predestination: inferring destinations from partial trajectories
UbiComp'06 Proceedings of the 8th international conference on Ubiquitous Computing
A system for destination and future route prediction based on trajectory mining
Pervasive and Mobile Computing
Pervasive and Mobile Computing
Ego network models for Future Internet social networking environments
Computer Communications
Breaking the habit: Measuring and predicting departures from routine in individual human mobility
Pervasive and Mobile Computing
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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.