ORBi: Hallot Pierre - A pyramidal classification of ST relationship models

Reference : A pyramidal classification of ST relationship models


	Document type :	Scientific congresses and symposiums : Paper published in a book
	Discipline(s) :	Engineering, computing & technology : Computer science Physical, chemical, mathematical & earth Sciences : Earth sciences & physical geography
	To cite this reference:	http://hdl.handle.net/2268/29435

Title :	A pyramidal classification of ST relationship models
Language :	English
Alternative title :	[fr] Une classification pyramidale des modèles de relations spatiotemporelles
Author, co-author :	Hallot, Pierre [Université de Liège - ULg > Département de géographie > Unité de Géomatique - Topographie et géométrologie >]
	Billen, Roland [Université de Liège - ULg > Département de géographie > Unité de Géomatique - Topographie et géométrologie >]
Publication date :	3-Nov-2009
Main document title :	Proceedings of the 3th Workshop on Behaviour Monitoring and Interpretation
Editor :	Van de Weghe, Nico
	Gottfried, Björn
	De Maeyer, Philippe
	Billen, Roland
On invitation :	No
Audience :	International
Event name :	3rd Workshop on Behaviour and Monitoring and Interpretation
Event date :	3 novembre 2009
Event organizer :	Ghent University, Belgium
Event place (city) :	Ghent
Event country :	Belgium
Keywords :	[fr] Science de l'information spatiale
	[en] spatiotemporal relationships ; spatiotemporal reasoning ; spatiotemporal information ; spatiotemporal history ; temporal spaces ; spatiotemporal clustering
Abstract :	[en] Although intensive works have been devoted to spatiotemporal modeling during the last two decades, there are only a few models dedicated to relationships between two (or more) moving objects. This paper proposes a classification framework of spatiotemporal relationship models based on the ways spatiotemporal histories are analyzed. First, we discuss model conditions of application. Then we propose a classification of spatiotemporal relationship models based on a pyramidal representation of the quantity of extracted information, i.e. the nature and the complexity of provided information, from spatiotemporal histories. This classification aims helping users to choose adequate models for their purposes. The proposed spatiotemporal histories analysis method could lead to the development of new spatiotemporal relationship models.
Target :	Researchers
Permalink :	http://hdl.handle.net/2268/29435
Other URL :	http://sunsite.informatik.rwth-aachen.de/Publications/CEUR-WS/Vol-541/

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Open access	BMI09_Hallot_Billen.pdf		Publisher postprint	142.07 kB	View/Open

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Restricted access	presentation_hallot_billen_BMI09.pptx	Presentation - slides	-	529.02 kB	Request copy

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