General spatial skyline operator

Lin, Q; Zhang, Y; Zhang, W; Li, A

General spatial skyline operator

Lin, Q Zhang, Y

Zhang, W Li, A

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Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, 7238 LNCS (PART 1), pp. 494 - 508
Issue Date:: 2012-05-11

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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	Li, A	en_US
dc.date.issued	2012-05-11	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2012, 7238 LNCS (PART 1), pp. 494 - 508	en_US
dc.identifier.isbn	9783642290374	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28953
dc.description.abstract	With the emergence of location-aware mobile device technologies, communication technologies and GPS systems, various location-aware queries have attracted great attentions in the database literature. In many user recommendation systems, the spatial preference query is used to suggest the objects based on their spatial proximity to the facilities. In this paper, we study the problem of general spatial skyline which can provide a minimal set of candidates that contain optimal solutions for any monotonic distance based spatial preference query. An efficient algorithm is proposed to significantly reduce the number of non-promising objects in the computation. The paper also covers a comprehensive performance study of the proposed techniques based on both real and synthetic data. © 2012 Springer-Verlag.	en_US
dc.relation.ispartof	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en_US
dc.relation.isbasedon	10.1007/978-3-642-29038-1_36	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	General spatial skyline operator	en_US
dc.type	Conference Proceeding
utslib.citation.volume	PART 1	en_US
utslib.citation.volume	7238 LNCS	en_US
utslib.for	0806 Information Systems	en_US
dc.location.activity	Busan, South Korea	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	PART 1	en_US
pubs.publication-status	Published	en_US
pubs.volume	7238 LNCS	en_US

Abstract:

With the emergence of location-aware mobile device technologies, communication technologies and GPS systems, various location-aware queries have attracted great attentions in the database literature. In many user recommendation systems, the spatial preference query is used to suggest the objects based on their spatial proximity to the facilities. In this paper, we study the problem of general spatial skyline which can provide a minimal set of candidates that contain optimal solutions for any monotonic distance based spatial preference query. An efficient algorithm is proposed to significantly reduce the number of non-promising objects in the computation. The paper also covers a comprehensive performance study of the proposed techniques based on both real and synthetic data. © 2012 Springer-Verlag.

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http://hdl.handle.net/10453/28953