Efficient construction of safe regions for moving kNN queries over dynamic datasets

Hasan, M; Cheema, MA; Lin, X; Zhang, Y

Efficient construction of safe regions for moving kNN queries over dynamic datasets

Hasan, M Cheema, MA Lin, X Zhang, Y

Permalink

Publication Type:: Conference Proceeding
Citation:: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009, 5644 LNCS pp. 373 - 379
Issue Date:: 2009-11-02

Closed Access

	Filename	Description	Size
	2013005470OK.pdf		212.43 kB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Hasan, M	en_US
dc.contributor.author	Cheema, MA	en_US
dc.contributor.author	Lin, X	en_US
dc.contributor.author	Zhang, Y https://orcid.org/0000-0002-2674-1638	en_US
dc.date.issued	2009-11-02	en_US
dc.identifier.citation	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009, 5644 LNCS pp. 373 - 379	en_US
dc.identifier.isbn	3642029817	en_US
dc.identifier.isbn	9783642029813	en_US
dc.identifier.issn	0302-9743	en_US
dc.identifier.uri	http://hdl.handle.net/10453/28965
dc.description.abstract	The concept of safe region has been used to reduce the computation and communication cost for the continuous monitoring of k nearest neighbor (kNN) queries. A safe region is an area such that as long as a query remains in it, the set of its kNNs does not change. In this paper, we present an efficient technique to construct the safe region by using cheap RangeNN queries. We also extend our approach for dynamic datasets (the objects may appear or disappear from the dataset). Our proposed algorithm outperforms existing algorithms and scales better with the increase in k. © 2009 Springer Berlin Heidelberg.	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	10.1007/978-3-642-02982-0_24	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Efficient construction of safe regions for moving kNN queries over dynamic datasets	en_US
dc.type	Conference Proceeding
utslib.citation.volume	5644 LNCS	en_US
utslib.for	0806 Information Systems	en_US
dc.location.activity	Aalborg, Denmark	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
pubs.volume	5644 LNCS	en_US

Abstract:

The concept of safe region has been used to reduce the computation and communication cost for the continuous monitoring of k nearest neighbor (kNN) queries. A safe region is an area such that as long as a query remains in it, the set of its kNNs does not change. In this paper, we present an efficient technique to construct the safe region by using cheap RangeNN queries. We also extend our approach for dynamic datasets (the objects may appear or disappear from the dataset). Our proposed algorithm outperforms existing algorithms and scales better with the increase in k. © 2009 Springer Berlin Heidelberg.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/28965