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Mining Moving Object Data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F11%3APU96184" target="_blank" >RIV/00216305:26230/11:PU96184 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Mining Moving Object Data

  • Original language description

    Currently there is a lot of devices that provide information about objects and this together with location-based services accumulate huge volume of moving object data, including trajectories. This paper deals with two useful analysis tasks - mining moving object data patterns and trajectory outlier detection. We also present our experience with the TOP-EYE trajectory outlier detection algorithm that we applied on two real-world data sets.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/VG20102015006" target="_blank" >VG20102015006: Tools and methods for video and image processing for the fight against terrorism</a><br>

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2011

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the Eleventh International Conference on Informatics

  • ISBN

    978-80-89284-94-8

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    16-21

  • Publisher name

    Faculty of Electrical Engineering and Informatics, University of Technology Košice

  • Place of publication

    Košice

  • Event location

    Rožňava

  • Event date

    Nov 16, 2011

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article