Abstract
With the development of wireless communications and embedded systems technologies, many smartphones are equipped with a multitude of sensors such as GPS and powerful computational, storage and communication capabilities. By these smartphones, location-based services provide the potentialto understand people's mobility pattern at an unprecedented level. How to discover people's personal mobility patterns is key phase for location-based services to provide high-quality service. Therefore, we focus on mining popular mobility patterns from user GPS trajectories. Firstly, we propose a transform method that transforms a GPS trajectory into a sequence of POI(points of interest) based on the spatial and temporal property of GPS points. Then, we propose a periodic-frequent POI sets mining method to discover the POI sets which are not only occurring frequently, but also appearing periodically. Finally, experimental results show the efficiency and stability of the algorithm.
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