Publication detail

Mining Moving Object Data

ZENDULKA, J. PEŠEK, M.

Original Title

Mining Moving Object Data

English Title

Mining Moving Object Data

Type

journal article - other

Language

en

Original Abstract

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

English abstract

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

Keywords

data mining, moving object data, trajectory, moving object patterns mining, trajectory outlier detection

RIV year

2012

Released

01.10.2012

Publisher

NEUVEDEN

Location

NEUVEDEN

ISBN

1896-1533

Periodical

Central European Journal of Computer Science

Year of study

2

Number

3

State

NL

Pages from

183

Pages to

193

Pages count

11

URL

Documents

BibTex


@article{BUT96931,
  author="Jaroslav {Zendulka} and Martin {Pešek}",
  title="Mining Moving Object Data",
  annote="Currently there is a lot of devices that provide information about moving objects
and location-based services that accumulate huge volume of moving object data,
including trajectories. This paper deals with two useful analysis tasks - mining
moving object patterns and trajectory outlier detection. We also present our
experience with the TOP-EYE trajectory outlier detection algorithm when we
applied it on two real-world data sets.",
  address="NEUVEDEN",
  chapter="96931",
  doi="10.2478/s13537-012-0018-4",
  edition="NEUVEDEN",
  howpublished="print",
  institution="NEUVEDEN",
  number="3",
  volume="2",
  year="2012",
  month="october",
  pages="183--193",
  publisher="NEUVEDEN",
  type="journal article - other"
}