Machine Learning
Navigate like a cabbie: probabilistic reasoning from observed context-aware behavior
UbiComp '08 Proceedings of the 10th international conference on Ubiquitous computing
CPL: Enhancing Mobile Phone Functionality by Call Predicted List
OTM '08 Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008 Workshops: ADI, AWeSoMe, COMBEK, EI2N, IWSSA, MONET, OnToContent + QSI, ORM, PerSys, RDDS, SEMELS, and SWWS
Context-aware taxi demand hotspots prediction
International Journal of Business Intelligence and Data Mining
T-drive: driving directions based on taxi trajectories
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Taxi-aware map: identifying and predicting vacant taxis in the city
AmI'10 Proceedings of the First international joint conference on Ambient intelligence
Proceedings of the 13th international conference on Ubiquitous computing
Where to find my next passenger
Proceedings of the 13th international conference on Ubiquitous computing
Pathlet learning for compressing and planning trajectories
Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
From taxi GPS traces to social and community dynamics: A survey
ACM Computing Surveys (CSUR)
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The analysis of taxi flow can help better understand the urban mobility. In this work, we analyze 177, 169 taxi trips collected in Lisbon, Portugal, to explore the relationships between pick-up and drop-off locations; the behavior between the previous drop-off to the following pick-up; and the impact of area type in taxi services. We also carry out the analysis of predictability of taxi trips given history of taxi flow in time and space.