Publication Details
Mining Moving Object Data
data mining, moving object, trajectory pattern, trajectory outlier
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.
Currently there is a lot of devices that provide information about objects 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 when we applied it on two real-world data sets.
@INPROCEEDINGS{FITPUB9799,
author = "Jaroslav Zendulka",
title = "Mining Moving Object Data",
pages = "16--21",
booktitle = "Proceedings of the Eleventh International Conference on Informatics",
year = 2011,
location = "Ko\v{s}ice, SK",
publisher = "Faculty of Electrical Engineering and Informatics, University of Technology Ko\v{s}ice",
ISBN = "978-80-89284-94-8",
language = "english",
url = "https://www.fit.vut.cz/research/publication/9799"
}