Journal article

ZENDULKA Jaroslav and PEŠEK Martin. Mining Moving Object Data. Central European Journal of Computer Science. 2012, vol. 2, no. 3, pp. 183-193. ISSN 1896-1533. Available from: http://link.springer.com/article/10.2478/s13537-012-0018-4
Publication language:english
Original title:Mining Moving Object Data
Title (cs):Dolování v datech pohybujících se objektů
Pages:183-193
Place:DE
Year:2012
URL:http://link.springer.com/article/10.2478/s13537-012-0018-4
Journal:Central European Journal of Computer Science, Vol. 2, No. 3, DE
ISSN:1896-1533
URL:http://link.springer.com/article/10.2478/s13537-012-0018-4 [HTML]
Keywords
data mining, moving object data, trajectory, moving object patterns mining, trajectory outlier detection
Annotation
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.
BibTeX:
@ARTICLE{
   author = {Jaroslav Zendulka and Martin Pe{\v{s}}ek},
   title = {Mining Moving Object Data},
   pages = {183--193},
   journal = {Central European Journal of Computer Science},
   volume = {2},
   number = {3},
   year = {2012},
   ISSN = {1896-1533},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php.en.iso-8859-2?id=9879}
}

Your IPv4 address: 54.226.227.175
Switch to IPv6 connection

DNSSEC [dnssec]