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Succinct Quadtrees for Road Data

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Similarity Search and Applications (SISAP 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10609))

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Abstract

We propose succinct quadtrees, space-efficient data structures for nearest point and segment queries in 2D space. We can compress both the tree structure and point coordinates and support fast queries. One important application is so called map matching, given GPS location data with errors, to correct errors by finding the nearest road. Experimental results show that our new data structure uses 1/25 working memory of a standard library for nearest point queries.

This work was supported by JST CREST Grant Number JPMJCR1402, Japan.

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Notes

  1. 1.

    http://www.dis.uniroma1.it/challenge9/download.shtml.

  2. 2.

    http://www.drm.jp/english/drm/e_index.htm.

  3. 3.

    http://www.cs.umd.edu/~mount/ANN/.

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Author information

Authors and Affiliations

  1. Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan

    Kazuki Ishiyama & Kunihiko Sadakane

  2. National Institute of Informatics, Tokyo, Japan

    Koji Kobayashi

Authors
  1. Kazuki Ishiyama
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  2. Koji Kobayashi
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  3. Kunihiko Sadakane
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Corresponding author

Correspondence to Kunihiko Sadakane .

Editor information

Editors and Affiliations

  1. Fraunhofer Institute for Applied Information Technology, Sankt Augustin, Germany

    Christian Beecks

  2. Ludwig-Maximilians-Universität München, Munich, Germany

    Felix Borutta

  3. Ludwig-Maximilians-Universität München, Munich, Germany

    Peer Kröger

  4. Ludwig-Maximilians-Universität München, Munich, Germany

    Thomas Seidl

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Ishiyama, K., Kobayashi, K., Sadakane, K. (2017). Succinct Quadtrees for Road Data. In: Beecks, C., Borutta, F., Kröger, P., Seidl, T. (eds) Similarity Search and Applications. SISAP 2017. Lecture Notes in Computer Science(), vol 10609. Springer, Cham. https://doi.org/10.1007/978-3-319-68474-1_18

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  • DOI: https://doi.org/10.1007/978-3-319-68474-1_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-68473-4

  • Online ISBN: 978-3-319-68474-1

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