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Flexible Pattern Queries

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Spatio-Temporal Databases

Part of the book series: SpringerBriefs in Computer Science ((BRIEFSCOMPUTER))

Abstract

The wide adaptation of GPS and cellular technologies has created many applications (e.g., location-based, tracking, geo-fencing, and surveillance) that collect and maintain large repositories of data in the form of trajectories. Each trajectory contains the spatial locations collected for a given moving object over an ordered sequence of time instants. Previous work on querying and analyzing trajectorial data typically falls into methods that either addresses spatial range and nearest neighbor queries, or similarity based queries. Nevertheless, trajectories are complex moving objects whose behavior over time and space can be better captured as a sequence of interesting events. We thus facilitate the use of motion pattern queries that allow the user to select trajectories based on specific motion patterns. Such patterns are described as regular expressions over a spatial alphabet that can be implicitly or explicitly anchored to the time domain. Moreover, we are interested in “flexible” patterns that allow the user to include variables in the pattern query, and thus greatly increase its expressive power. In this chapter, we present a system called FlexTrack for efficient processing of flexible pattern queries. FlexTrack includes an underlying indexing structure and algorithms for query processing using different evaluation strategies. Using both synthetic and real datasets an extensive performance evaluation of the FlexTrack system shows significant performance improvement when compared to baseline approaches.

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Authors and Affiliations

  1. IBM Research Laboratory Brazil, Rio de Janeiro, RJ, Brazil

    Marcos R. Vieira

  2. Department of Computer Science and Engineering, Bourns College of Engineering, University of California, Riverside, CA, USA

    Vassilis J. Tsotras

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  1. Marcos R. Vieira
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Vieira, M.R., Tsotras, V.J. (2013). Flexible Pattern Queries. In: Spatio-Temporal Databases. SpringerBriefs in Computer Science. Springer, Cham. https://doi.org/10.1007/978-3-319-02408-0_2

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