DocumentCode
2714101
Title
Invited seminar abstracts
Author
Trajcevski, G. ; Gunopulos, Dimitrios
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., Northwestern Univ., Evanston, IL, USA
fYear
2010
fDate
23-26 May 2010
Abstract
The main motivation for this tutorial is that one particular property of the mobile entities - their similarity, has been of interest in wide range of application domains where some form of location-based awareness is needed. The objective of this tutorial is to give an overview of the different facets of the problem of detecting the similarity among moving objects´ trajectories. Specifically, different techniques are presented for assessing the similarity and identify the implications that different applications context(s) have on the specific approaches. The article also discuss the impact of the similarity-based mining/clustering of spatiotemporal data on applications that have large societal impacts, such as efficient traffic management and disaster remediation.
Keywords
data mining; mobile computing; motion estimation; pattern clustering; location-based awareness; mobile entities; motion similarity; moving object trajectories; similarity detection; similarity-based clustering; similarity-based mining; spatiotemporal data;
fLanguage
English
Publisher
ieee
Conference_Titel
Mobile Data Management (MDM), 2010 Eleventh International Conference on
Conference_Location
Kansas City, MO
Print_ISBN
978-1-4244-7075-4
Type
conf
DOI
10.1109/MDM.2010.81
Filename
5489772
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