Publication detail

Mining Moving Object Data

ZENDULKA, J.

Original Title

Mining Moving Object Data

English Title

Mining Moving Object Data

Type

conference paper

Language

en

Original Abstract

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.

English abstract

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.

Keywords

data mining, moving object, trajectory pattern, trajectory outlier

RIV year

2011

Released

15.11.2011

Publisher

Faculty of Electrical Engineering and Informatics, University of Technology Košice

Location

Košice

ISBN

978-80-89284-94-8

Book

Proceedings of the Eleventh International Conference on Informatics

Edition

NEUVEDEN

Edition number

NEUVEDEN

Pages from

16

Pages to

21

Pages count

6

BibTex


@inproceedings{BUT76480,
  author="Jaroslav {Zendulka}",
  title="Mining Moving Object Data",
  annote="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.",
  address="Faculty of Electrical Engineering and Informatics, University of Technology Košice",
  booktitle="Proceedings of the Eleventh International Conference on Informatics",
  chapter="76480",
  edition="NEUVEDEN",
  howpublished="print",
  institution="Faculty of Electrical Engineering and Informatics, University of Technology Košice",
  year="2011",
  month="november",
  pages="16--21",
  publisher="Faculty of Electrical Engineering and Informatics, University of Technology Košice",
  type="conference paper"
}