Mining Popular Mobility Patterns from User GPS Trajectories

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 understan...

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Bibliographic Details
Published in2016 9th International Conference on Service Science (ICSS) pp. 180 - 181
Main Authors Zhou Fang, Chao Ma, Xizhong Wang, Jiaxing Qu
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.10.2016
Subjects
Data mining
Geology
Global Positioning System
GPS trajectories
History
mobility patterns
periodic-frequent mining
points of interest
Smart phones
Trajectory
Transportation
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Summary: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.
ISSN:2165-3836
DOI:10.1109/ICSS.2016.33