References
Cheng R, Kalashnikov, DV, Prabhakar, S (2004) Querying imprecise data in moving object environments. IEEE Trans Knowl Data Eng 16(9):1112–1127
Deng K, Xie K, Zheng K, Zhou X (2011) Trajectory indexing and retrieval. Computing with spatial trajectories. Springer, New York, pp 35–60
Draxler RR, Rolph, GD (2003) Hysplit (hybrid single-particle lagrangian integrated trajectory). NOAA air resources laboratory, silver spring, MD. model access via NOAA ARL ready website
Koide S, Tadokoro Y, Xiao C, Ishikawa Y (2017) CiNCT: compression and retrieval for massive vehicular trajectories via relative movement labeling. arXiv preprint arXiv:1706.02885
Lee J-G, Han J, Whang K-Y (2007) Trajectory clustering: a partition-and-group framework. In: Proceedings of the 2007 ACM SIGMOD international conference on Management of data. ACM, pp 593–604
Li Z, Ding B, Han J, Kays R (2010a) Swarm: mining relaxed temporal moving object clusters. Proc VLDB Endow 3(1–2):723–734
Li Z, Ding B, Han J, Kays R, Nye P (2010b) Mining periodic behaviors for moving objects. In: Proceedings of the 16th ACM SIGKDD international conference on knowledge discovery and data mining. ACM, pp 1099–1108
Song R, Sun W, Zheng B, Zheng Y (2014) Press: a novel framework of trajectory compression in road networks. Proc VLDB Endow 7(9):661–672
Su H, Zheng K, Wang H, Huang J, Zhou X (2013) Calibrating trajectory data for similarity-based analysis. In: Proceedings of the 2013 ACM SIGMOD international conference on management of data. ACM, pp 833–844
Tao Y, Papadias D (2001) The mv3r-tree: a spatio-temporal access method for timestamp and interval queries. In: Proceedings of very large data bases conference (VLDB), 11–14 Sept, Rome
Wang H, Su H, Zheng K, Sadiq S, Zhou X (2013) An effectiveness study on trajectory similarity measures. In: Proceedings of the twenty-fourth Australasian database conference, vol 137. Australian Computer Society, Inc., pp 13–22
Yang B, Guo C, Jensen CS (2013) Travel cost inference from sparse, spatio temporally correlated time series using Markov models. Proc VLDB Endow 6(9): 769–780
Yuan J, Zheng Y, Xie X, Sun G (2013) T-drive: enhancing driving directions with taxi drivers’ intelligence. IEEE Trans Knowl Data Eng 25(1):220–232
Zheng Y (2015) Trajectory data mining: an overview. ACM Trans Intell Syst Technol (TIST) 6(3):29
Zheng Y, Xie X (2011) Learning travel recommendations from user-generated GPS traces. ACM Trans Intell Syst Technol (TIST) 2(1):2
Zheng Y, Zhou X (2011) Computing with spatial trajectories. Springer Science & Business Media, New York
Zheng K, Zheng Y, Xie X, Zhou X (2012) Reducing uncertainty of low-sampling-rate trajectories. In: 2012 IEEE 28th international conference on data engineering (ICDE). IEEE, pp 1144–1155
Zheng K, Zheng Y, Yuan NJ, Shang S, Zhou X (2014) Online discovery of gathering patterns over trajectories. IEEE Trans Knowl Data Eng 26(8):1974–1988
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Zhou, X., Li, L. (2018). Spatiotemporal Data: Trajectories. In: Sakr, S., Zomaya, A. (eds) Encyclopedia of Big Data Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-63962-8_221-1
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DOI: https://doi.org/10.1007/978-3-319-63962-8_221-1
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Spatio-Temporal Data - From Trajectory Management to Mining- Published:
- 25 February 2022
DOI: https://doi.org/10.1007/978-3-319-63962-8_221-2
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Spatiotemporal Data: Trajectories- Published:
- 01 February 2018
DOI: https://doi.org/10.1007/978-3-319-63962-8_221-1