In this paper, we propose a new spatio-temporal similarity measure to compute spatio-temporal relevance between two trajectories of moving objects on road networks, which is known as spatio-temporal distance (STDist). In addition, we provide a similar trajectory search algorithm to retrieve similar trajectories based on the proposed measure i.e., a combination of both spatial and temporal properties with respect to the motion of a given query trajectory. The performance evaluation shows that our approach outperforms the existing work in terms of searching similar trajectories of moving objects on road networks. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Chang, J. W., Bista, R., Kim, Y. C., & Kim, Y. K. (2007). Spatio-temporal similarity measure algorithm for moving objects on spatial networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4707 LNCS, pp. 1165–1178). Springer Verlag. https://doi.org/10.1007/978-3-540-74484-9_102
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