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A new trajectory search algorithm based on spatio-temporal similarity on spatial network

  • Jae Woo Chang*
  • , Rabindra Bista
  • , Ji Hee Kim
  • , Young Chang Kim
  • *Corresponding author for this work
    • Jeonbuk National University

    Research output: Contribution to conferenceConference paperpeer-review

    Abstract

    In this paper, we define a new measure to compute spatio-temporal similarity between two trajectories of moving objects on road networks, which is known as spatio-temporal distance (STDist). In addition, we propose a new spatio-temporal similar trajectory search algorithm to retrieve similar trajectories based on the spatio-temporal distance, a combination of both spatial and temporal properties with respect to the motion of a given query trajectory. To support fast trajectories retrieval, we use a signature file method in which we generate signatures for segments of a trajectory. Our performance analysis shows that our algorithm outperforms the existing method in terms of searching similar trajectories of moving objects on road network.

    Original languageEnglish
    Title of host publicationCIT 2007
    Subtitle of host publication7th IEEE International Conference on Computer and Information Technology
    Pages110-115
    Number of pages6
    DOIs
    StatePublished - 2007
    EventCIT 2007: 7th IEEE International Conference on Computer and Information Technology - Aizu-Wakamatsu, Fukushima, Japan
    Duration: 2007.10.162007.10.19

    Publication series

    NameCIT 2007: 7th IEEE International Conference on Computer and Information Technology

    Conference

    ConferenceCIT 2007: 7th IEEE International Conference on Computer and Information Technology
    Country/TerritoryJapan
    CityAizu-Wakamatsu, Fukushima
    Period07.10.1607.10.19

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 11 - Sustainable Cities and Communities
      SDG 11 Sustainable Cities and Communities

    Quacquarelli Symonds(QS) Subject Topics

    • Computer Science & Information Systems
    • Mathematics
    • Data Science

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