Abstract
With the rapid development of mobile computing and Web services, a huge amount of data with spatial and temporal information have been collected everyday by smart mobile terminals, in which an object is described by its spatial information and temporal information. Motivated by the significance of spatio-temporal range search and the lack of efficient search algorithm, in this paper, we study the problem of spatio-temporal range search (STRS), a novel index structure is proposed, called HOC-Tree, which is based on Hilbert curve and OC-Tree, and takes both spatial and temporal information into consideration. Based on HOC-Tree, we develop an efficient algorithm to solve the problem of spatio-temporal range search. Comprehensive experiments on real and synthetic data demonstrate that our method is more efficient than the state-of-the-art technique.
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Acknowledgments
This work was supported in part by the National Natural Science Foundation of China (61702560, 61379110, 61472450), the Key Research Program of Hunan Province (2016JC2018), Natural Science Foundation of Hunan Province (2018JJ3691), and Science and Technology Plan of Hunan Province (2016JC2011).
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Long, J., Zhu, L., Zhang, C., Lin, S., Yang, Z., Yuan, X. (2018). HOC-Tree: A Novel Index for Efficient Spatio-Temporal Range Search. In: Ganji, M., Rashidi, L., Fung, B., Wang, C. (eds) Trends and Applications in Knowledge Discovery and Data Mining. PAKDD 2018. Lecture Notes in Computer Science(), vol 11154. Springer, Cham. https://doi.org/10.1007/978-3-030-04503-6_8
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DOI: https://doi.org/10.1007/978-3-030-04503-6_8
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