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Australasian Database Conference

ADC 2017: Databases Theory and Applications pp 29–41Cite as

Boosting Point-Based Trajectory Search with Quad-Tree

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10538))

Abstract

The availability of spatial data generated by objects enables people to search for a similar pattern using a set of query points. In this paper, we focus on point-based trajectory search problem which returns top-k results to a set of query points. The primary purpose of this work is to revisit state-of-the-art search algorithms on various indices and find the best choice of spatial index while giving a reason behind it. Furthermore, we propose an optimization on the search method, which is able to find the initial upper bound for the query points, leading to further performance improvement. Lastly, extensive experiments on real dataset verified the choice of the index and our proposed search method.

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Acknowledgment

Zhifeng Bao is partially supported by ARC DP170102726 and Google Faculty Research Award. Munkh-Erdene Yadamjav is a recipient of Data61 PhD Scholarship.

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Authors and Affiliations

  1. RMIT University, Melbourne, Australia

    Munkh-Erdene Yadamjav, Sheng Wang & Zhifeng Bao

  2. DATA61 — CSIRO, Canberra, Australia

    Bang Zhang

Authors
  1. Munkh-Erdene Yadamjav
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  2. Sheng Wang
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  3. Zhifeng Bao
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  4. Bang Zhang
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Corresponding author

Correspondence to Munkh-Erdene Yadamjav .

Editor information

Editors and Affiliations

  1. University of Queensland, Brisbane, Queensland, Australia

    Zi Huang

  2. Nanyang Technological University, Singapore, Singapore

    Xiaokui Xiao

  3. University of New South Wales, Sydney, New South Wales, Australia

    Xin Cao

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Yadamjav, ME., Wang, S., Bao, Z., Zhang, B. (2017). Boosting Point-Based Trajectory Search with Quad-Tree. In: Huang, Z., Xiao, X., Cao, X. (eds) Databases Theory and Applications. ADC 2017. Lecture Notes in Computer Science(), vol 10538. Springer, Cham. https://doi.org/10.1007/978-3-319-68155-9_3

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  • DOI: https://doi.org/10.1007/978-3-319-68155-9_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68154-2

  • Online ISBN: 978-3-319-68155-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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