A Survey on Trajectory Data Mining: Techniques and Applications

Rapid advance of location acquisition technologies boosts the generation of trajectory data, which track the traces of moving objects. A trajectory is typically represented by a sequence of timestamped geographical locations. A wide spectrum of applications can benefit from the trajectory data minin...

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Bibliographic Details
Published in:IEEE access 2016-01, Vol.4, p.2056-2067
Main Authors: Feng, Zhenni, Zhu, Yanmin
Format: Article
Language:English
Subjects:
Big data
big data applications
Data analytics
Data mining
data mining techniques
Data processing
Geographical locations
Location awareness
Moving object recognition
Trajectories
Trajectory
Trajectory data mining
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Summary:Rapid advance of location acquisition technologies boosts the generation of trajectory data, which track the traces of moving objects. A trajectory is typically represented by a sequence of timestamped geographical locations. A wide spectrum of applications can benefit from the trajectory data mining. Bringing unprecedented opportunities, large-scale trajectory data also pose great challenges. In this paper, we survey various applications of trajectory data mining, e.g., path discovery, location prediction, movement behavior analysis, and so on. Furthermore, this paper reviews an extensive collection of existing trajectory data mining techniques and discusses them in a framework of trajectory data mining. This framework and the survey can be used as a guideline for designing future trajectory data mining solutions.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2016.2553681