Similarity search algorithm for efficient sub-trajectory matching in moving databases

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Abstract

Similarity measure scheme on moving objects has become a topic of increasing in the area of moving databases. In this paper, we propose a new similarity search algorithm for efficient sub-trajectory matching. For measuring similarity between two sub-trajectories, we propose a new v(variable)-warping distance algorithm which enhances the existing time warping distance algorithm by permitting up to v replications for an arbitrary motion of a query trajectory. Our v-warping distance algorithm provides an approximate matching between two trajectories as well as an exact matching between them. Based on our vwarping distance algorithm, we also present a similarity measure scheme for the single trajectory in moving databases. Finally, we show that our scheme based on the v-warping distance achieves much better performance than other conventional schemes, such as Li's one (no-warping) and Shan's one (infinitewarping) in terms of precision and recall measures. © Springer-Verlag Berlin Heidelberg 2007.

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APA

Lim, E. C., & Shim, C. B. (2007). Similarity search algorithm for efficient sub-trajectory matching in moving databases. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4489 LNCS, pp. 821–828). Springer Verlag. https://doi.org/10.1007/978-3-540-72588-6_132

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