Efficient general spatial skyline computation

Lin, Q; Zhang, Y; Zhang, W; Lin, X

Efficient general spatial skyline computation

Lin, Q Zhang, Y

Zhang, W Lin, X

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Publication Type:: Journal Article
Citation:: World Wide Web, 2013, 16 (3), pp. 247 - 270
Issue Date:: 2013-01-01

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Field	Value	Language
dc.contributor.author	Lin, Q	en_US
dc.contributor.author	Zhang, Y https://orcid.org/0000-0002-2674-1638	en_US
dc.contributor.author	Zhang, W	en_US
dc.contributor.author	Lin, X	en_US
dc.date.issued	2013-01-01	en_US
dc.identifier.citation	World Wide Web, 2013, 16 (3), pp. 247 - 270	en_US
dc.identifier.issn	1386-145X	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28918
dc.description.abstract	With the emergence of location-aware mobile device technologies, communication technologies and GPS systems, the location based queries have attracted great attentions in the database literature. In many user recommendation web services, the spatial preference query is used to suggest the objects based on their spatial proximity with the facilities. In this paper, we study the problem of general spatial skyline (GSSKY) which can provide the minimal candidate set of the optimal solutions for any monotonic distance based spatial preference query. Efficient progressive algorithm called P-GSSKY is proposed to significantly reduce the number of non-promising objects in the computation. Moreover, we also propose spatial join based algorithm, called J-GSSKY, which can compute GSSKY efficiently in terms of I/O cost. The paper conducts a comprehensive performance study of the proposed techniques based on both real and synthetic data. © 2012 Springer Science+Business Media, LLC.	en_US
dc.relation.ispartof	World Wide Web	en_US
dc.relation.isbasedon	10.1007/s11280-012-0185-1	en_US
dc.subject.classification	Information Systems	en_US
dc.title	Efficient general spatial skyline computation	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	16	en_US
utslib.for	0806 Information Systems	en_US
utslib.for	0804 Data Format	en_US
utslib.for	0805 Distributed Computing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CAI - Centre for Artificial Intelligence
utslib.copyright.status	closed_access
pubs.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	16	en_US

Abstract:

With the emergence of location-aware mobile device technologies, communication technologies and GPS systems, the location based queries have attracted great attentions in the database literature. In many user recommendation web services, the spatial preference query is used to suggest the objects based on their spatial proximity with the facilities. In this paper, we study the problem of general spatial skyline (GSSKY) which can provide the minimal candidate set of the optimal solutions for any monotonic distance based spatial preference query. Efficient progressive algorithm called P-GSSKY is proposed to significantly reduce the number of non-promising objects in the computation. Moreover, we also propose spatial join based algorithm, called J-GSSKY, which can compute GSSKY efficiently in terms of I/O cost. The paper conducts a comprehensive performance study of the proposed techniques based on both real and synthetic data. © 2012 Springer Science+Business Media, LLC.

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http://hdl.handle.net/10453/28918