PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
A Column-Generation Approach to Line Planning in Public Transport
Transportation Science
Ocean of information: fusing aggregate & individual dynamics for metropolitan analysis
Proceedings of the 15th international conference on Intelligent user interfaces
Unveiling the complexity of human mobility by querying and mining massive trajectory data
The VLDB Journal — The International Journal on Very Large Data Bases
Estimating Origin-Destination Flows Using Mobile Phone Location Data
IEEE Pervasive Computing
Proceedings of the 2013 international conference on Intelligent user interfaces
Visual Exploration of Big Spatio-Temporal Urban Data: A Study of New York City Taxi Trips
IEEE Transactions on Visualization and Computer Graphics
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The deep penetration of mobile phones offers cities the ability to opportunistically monitor citizensfi mobility and use data-driven insights to better plan and manage services. In this context, transit operators can leverage pervasive mobile sensing to better match observed demand for travel with their service offerings. In this paper we present AllAboard, an intelligent tool that analyses cellphone data to helps city authorities in exploring urban mobility and optimizing public transport. An interactive user interface allows transit operators to explore the travel demand in both space and time, evaluate the quality of service that a transit network provides to the citizens, and test scenarios for transit network improvements. The system has been tested using real telecommunication data for the city of Abidjan, Ivory Coast, and evaluated from a data mining, optimization and user prospective.