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Tang L A, Zheng Y, Yuan J, et al. A framework of traveling companion discovery on trajectory data streams[J]. ACM Transactions on Intelligent Systems and Technology, 2013, 5(1): 992-999.
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Tang L A, Zheng Y, Yuan J, et al. On discovery of traveling companions from streaming trajectories[C]// Proceedings of the International Conference on Data Engineering. Arlington, USA: IEEE Press, 2012: 186-197.
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Zheng Y, Yuan N J, Zheng K, et al. On discovery of gathering patterns from trajectories[J]. nternational Conference on Data Engineering, 2013, 26(8): 242-253.
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Kalnis P, Mamoulis N, Bakiras S. On discovering moving clusters in spatio-temporal data[C]// Proceedings of the 9th International Conference on Advances in spatial and temporal databases. Springer, 2005: 364-381.
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Zhang J M, Li J L, Wang S G, et al. On retrieving moving objects gathering patterns from trajectory data via spatio-temporal graph[C]// IEEE International Congress on Big Data. Anchorage, USA: IEEE Press, 2014: 390-397.
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Yoo J S, Boulware D, Kimmey D. A parallel spatial co-location mining algorithm based on MapReduce[C]// IEEE International Congress on Big Data. Anchorage, USA: IEEE Press, 2014: 25-31.
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Yu Y W, Wang Q, Wang X D. Continuous clustering trajectory stream of moving objects[J]. Communications, 2013, 10(9): 120-129.
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Yu Y W, Wang Q, Wang X D, et al. Online clustering for trajectory data stream of moving objects[J]. Computer Science and Information Systems, 2013, 10(3): 1293-1317.
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Mertens S. The Easiest Hard Problem: Number Partitioning[A]// Computational Complexity and Statistical Physics. 2003: 125-140.
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S. S. Skiena. The Algorithm Design Manual[Z]. 2ed, Springer, 2008: 294-298.
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Kemmerer B. SPARK[EB/OL]. http://spark.apache.org/ last retrieved at 2015/1/10.
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Cosmides L, Tooby J. Are humans good intuitive statisticians after all? Rethinking some conclusions from the literature on judgment under uncertainty[J]. Cognition, 1996, 58(1): 1-73.)
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[1] |
Gudmundsson J M, van Kreveld M. Computing longest duration flocks in trajectory data[C]// Proceedings of the 14th Annual ACM International Symposium on Advances in Geographic Information Systems. Arlington, USA: ACM Press, 2006: 35-42.
|
[2] |
Jeung H, Yiu M L, Zhou X F, et al. Discovery of convoys in trajectory databases[J]. Proceedings of the VLDB Endowment, 2008,1(1): 1068-1080.
|
[3] |
Li Z H, Ding B L, Han J W, et al. Swarm: Mining relaxed temporal moving object clusters accurate discovery of valid convoys from moving object trajectories[C]// Proceedings of International Conference on Very Large Data Base. Springer-Verlag, 2010: 723-734.
|
[4] |
Tang L A, Zheng Y, Yuan J, et al. A framework of traveling companion discovery on trajectory data streams[J]. ACM Transactions on Intelligent Systems and Technology, 2013, 5(1): 992-999.
|
[5] |
Tang L A, Zheng Y, Yuan J, et al. On discovery of traveling companions from streaming trajectories[C]// Proceedings of the International Conference on Data Engineering. Arlington, USA: IEEE Press, 2012: 186-197.
|
[6] |
Zheng Y, Yuan N J, Zheng K, et al. On discovery of gathering patterns from trajectories[J]. nternational Conference on Data Engineering, 2013, 26(8): 242-253.
|
[7] |
Kalnis P, Mamoulis N, Bakiras S. On discovering moving clusters in spatio-temporal data[C]// Proceedings of the 9th International Conference on Advances in spatial and temporal databases. Springer, 2005: 364-381.
|
[8] |
Zhang J M, Li J L, Wang S G, et al. On retrieving moving objects gathering patterns from trajectory data via spatio-temporal graph[C]// IEEE International Congress on Big Data. Anchorage, USA: IEEE Press, 2014: 390-397.
|
[9] |
Yoo J S, Boulware D, Kimmey D. A parallel spatial co-location mining algorithm based on MapReduce[C]// IEEE International Congress on Big Data. Anchorage, USA: IEEE Press, 2014: 25-31.
|
[10] |
Yu Y W, Wang Q, Wang X D. Continuous clustering trajectory stream of moving objects[J]. Communications, 2013, 10(9): 120-129.
|
[11] |
Yu Y W, Wang Q, Wang X D, et al. Online clustering for trajectory data stream of moving objects[J]. Computer Science and Information Systems, 2013, 10(3): 1293-1317.
|
[12] |
Mertens S. The Easiest Hard Problem: Number Partitioning[A]// Computational Complexity and Statistical Physics. 2003: 125-140.
|
[13] |
S. S. Skiena. The Algorithm Design Manual[Z]. 2ed, Springer, 2008: 294-298.
|
[14] |
Kemmerer B. SPARK[EB/OL]. http://spark.apache.org/ last retrieved at 2015/1/10.
|
[15] |
Cosmides L, Tooby J. Are humans good intuitive statisticians after all? Rethinking some conclusions from the literature on judgment under uncertainty[J]. Cognition, 1996, 58(1): 1-73.)
|