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Indexing Multi-Dimensional Trajectories for Similarity Queries

Indexing Multi-Dimensional Trajectories for Similarity Queries

Michail Valachos, Marios Hadjieleftheriou, Eamonn Keogh, Dimitrios Gunopulos
Copyright: © 2005 |Pages: 23
ISBN13: 9781591403876|ISBN10: 1591403871|ISBN13 Softcover: 9781591403883|EISBN13: 9781591403890
DOI: 10.4018/978-1-59140-387-6.ch005
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MLA

Valachos, Michail, et al. "Indexing Multi-Dimensional Trajectories for Similarity Queries." Spatial Databases: Technologies, Techniques and Trends, edited by Yannis Manalopoulos, et al., IGI Global, 2005, pp. 107-129. https://doi.org/10.4018/978-1-59140-387-6.ch005

APA

Valachos, M., Hadjieleftheriou, M., Keogh, E., & Gunopulos, D. (2005). Indexing Multi-Dimensional Trajectories for Similarity Queries. In Y. Manalopoulos, A. Papadopoulos, & M. Vassilakopoulos (Eds.), Spatial Databases: Technologies, Techniques and Trends (pp. 107-129). IGI Global. https://doi.org/10.4018/978-1-59140-387-6.ch005

Chicago

Valachos, Michail, et al. "Indexing Multi-Dimensional Trajectories for Similarity Queries." In Spatial Databases: Technologies, Techniques and Trends, edited by Yannis Manalopoulos, Apostolos Papadopoulos, and Michael Gr. Vassilakopoulos, 107-129. Hershey, PA: IGI Global, 2005. https://doi.org/10.4018/978-1-59140-387-6.ch005

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Abstract

With the abundance of low-cost storage devices, a plethora of applications that store and manage very large multi-dimensional trajectories (or time-series) datasets have emerged recently. Examples include traffic supervision systems, video surveillance applications, meteorology and more. Thus, it is becoming essential to provide a robust trajectory indexing framework designed especially for performing similarity queries in such applications. In this regard, this chapter presents an indexing scheme that can support a wide variety of (user-customizable) distance measures while, at the same time, it guarantees retrieval of similar trajectories with accuracy and efficiency.

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