Uncertain location based range aggregates in a multi-dimensional space

Zhang, Y; Lin, X; Tao, Y; Zhang, W

Uncertain location based range aggregates in a multi-dimensional space

Zhang, Y

Lin, X Tao, Y Zhang, W

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Publication Type:: Conference Proceeding
Citation:: Proceedings - International Conference on Data Engineering, 2009, pp. 1247 - 1250
Issue Date:: 2009-07-08

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Field	Value	Language
dc.contributor.author	Zhang, Y https://orcid.org/0000-0002-2674-1638	en_US
dc.contributor.author	Lin, X	en_US
dc.contributor.author	Tao, Y	en_US
dc.contributor.author	Zhang, W	en_US
dc.date.issued	2009-07-08	en_US
dc.identifier.citation	Proceedings - International Conference on Data Engineering, 2009, pp. 1247 - 1250	en_US
dc.identifier.isbn	9780769535456	en_US
dc.identifier.issn	1084-4627	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28967
dc.description.abstract	Uncertain data are inherent in many applications such as environmental surveillance and quantitative economics research. Recently, considerable research efforts have been put into the field of analysing uncertain data. In this paper, we study the problem of processing the uncertain location based range aggregate in a multi-dimensional space. We first formally introduce the problem, then propose a general filtering-and-verification framework to solve the problem. Two filtering techniques, named STF and PCR respectively, are proposed to significantly reduce the verification cost. © 2009 IEEE.	en_US
dc.relation.ispartof	Proceedings - International Conference on Data Engineering	en_US
dc.relation.isbasedon	10.1109/ICDE.2009.212	en_US
dc.title	Uncertain location based range aggregates in a multi-dimensional space	en_US
dc.type	Conference Proceeding
utslib.for	0806 Information Systems	en_US
dc.location.activity	Shanghai, China	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.publication-status	Published	en_US

Abstract:

Uncertain data are inherent in many applications such as environmental surveillance and quantitative economics research. Recently, considerable research efforts have been put into the field of analysing uncertain data. In this paper, we study the problem of processing the uncertain location based range aggregate in a multi-dimensional space. We first formally introduce the problem, then propose a general filtering-and-verification framework to solve the problem. Two filtering techniques, named STF and PCR respectively, are proposed to significantly reduce the verification cost. © 2009 IEEE.

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http://hdl.handle.net/10453/28967