Abstract
Huge amount of location and tracking data is gathered by location and tracking technologies, such as global positioning system (GPS) and global system for mobile communication (GSM) devices; leading to the collection of large spatiotemporal datasets and to the opportunity of discovering usable knowledge about movement behavior. Movement behavior can be extremely useful in many ways when applied, for example, in the domain of traffic management, planning metropolitan areas, mobile marketing, tourism, etc. In this research, we move towards this direction and propose a framework for finding trajectory patterns of frequent behaviors using GSM data. The research question is "how to use trajectory data analysis in support of solving traffic management problems utilizing data mining techniques?" Our framework is illustrated to explain how GSM data can provide accurate information about population movement behavior, and hence support traffic decisions.
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Elragal, A., Raslan, H. (2014). Analysis of Trajectory Data in Support of Traffic Management: A Data Mining Approach. In: Perner, P. (eds) Advances in Data Mining. Applications and Theoretical Aspects. ICDM 2014. Lecture Notes in Computer Science(), vol 8557. Springer, Cham. https://doi.org/10.1007/978-3-319-08976-8_13
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DOI: https://doi.org/10.1007/978-3-319-08976-8_13
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08975-1
Online ISBN: 978-3-319-08976-8
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