Abstract
With the developments of the mobile devices and Internet of things, the location data have recorded amount of information about people activities. Mining the hot spots from the location-based data and studying the changing patterns of hot spots are useful to the early warnings of the disasters, traffic jams and crimes. Current researches on hot spots detections ignore the temporal factors. In this paper, the data field method is used to describe the interactions of spots, and the temporal factors are incorporated into the data field method. Furthermore, a hot spots detection method is proposed. Finally, the heat map is used to illustrate the effectiveness of the proposed method based on an open dataset.
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Acknowledgement
This work is supported by National Natural Science Foundation of China (No. 61502246), NUPTSF (No. NY215019).
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Wu, Z., Chen, J. (2020). Detecting Hot Spots Using the Data Field Method. In: Liu, Q., Mısır, M., Wang, X., Liu, W. (eds) The 8th International Conference on Computer Engineering and Networks (CENet2018). CENet2018 2018. Advances in Intelligent Systems and Computing, vol 905. Springer, Cham. https://doi.org/10.1007/978-3-030-14680-1_7
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DOI: https://doi.org/10.1007/978-3-030-14680-1_7
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