Bridging the gap between physical location and online social networks
Proceedings of the 12th ACM international conference on Ubiquitous computing
TaskShadow: Toward Seamless Task Migration across Smart Environments
IEEE Intelligent Systems
Urban mobility study using taxi traces
Proceedings of the 2011 international workshop on Trajectory data mining and analysis
Proceedings of the 13th international conference on Ubiquitous computing
iBAT: detecting anomalous taxi trajectories from GPS traces
Proceedings of the 13th international conference on Ubiquitous computing
Estimating Origin-Destination Flows Using Mobile Phone Location Data
IEEE Pervasive Computing
Trip analyzer through smartphone apps
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Prediction of urban human mobility using large-scale taxi traces and its applications
Frontiers of Computer Science in China
ScudWare: A Semantic and Adaptive Middleware Platform for Smart Vehicle Space
IEEE Transactions on Intelligent Transportation Systems
Discovering regions of different functions in a city using human mobility and POIs
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
coRide: carpool service with a win-win fare model for large-scale taxicab networks
Proceedings of the 11th ACM Conference on Embedded Networked Sensor Systems
From taxi GPS traces to social and community dynamics: A survey
ACM Computing Surveys (CSUR)
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Origin-destination(OD) flows reflect both human activity and urban dynamic in a city. However, our understanding about their patterns remains limited. In this paper, we study the GPS traces of taxis in a city with several millions people, China and find that there are significant patterns under the OD flows constructed from taxis' random motion. Our spatiotemporal analysis shows that those patterns have close relationship with the semantics of OD flows, hence we can mine the semantics of OD flows from raw GPS trace data. The approach we proposed offers a novel way to explore the human mobility and location characteristic.