Abstract
Driven by the GPS-enabled devices and wireless communication technologies, the researches and applications on spatio-temporal databases have received significant attention during the past decade. Hence, large trajectory datasets are extremely necessary to test high performance algorithms for these applications and researches. However, real-world datasets are not accessible in many cases due to privacy concerns and business competition. For this reason, we propose a practical model FTS to generate new trajectories in this work. We generate new trajectories based on features extracted from original dataset and validate the result by comparing the features of generated trajectories with the given dataset finally.
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Acknowledgement
This work was supported by the National Natural Science Foundation of China under Grant Nos. 61572335, 61572336, and 61303019, the Natural Science Foundation of Jiangsu Province of China under Grant No. BK20151223, the Natural Science Foundation of Jiangsu Provincial Department of Education of China under Grant No. 12KJB520017, and Collaborative Innovation Center of Novel Software Technology and Industrialization, Jiangsu, China.
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Li, J., Chen, W., Liu, A., Li, Z., Zhao, L. (2016). FTS: A Practical Model for Feature-Based Trajectory Synthesis. In: Li, F., Shim, K., Zheng, K., Liu, G. (eds) Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science(), vol 9931. Springer, Cham. https://doi.org/10.1007/978-3-319-45814-4_3
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DOI: https://doi.org/10.1007/978-3-319-45814-4_3
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