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Conference Paper: Common influence join: A natural join operation for spatial pointsets

TitleCommon influence join: A natural join operation for spatial pointsets
Authors
Issue Date2008
Citation
Proceedings - International Conference On Data Engineering, 2008, p. 100-109 How to Cite?
AbstractWe identify and formalize a novel join operator for two spatial pointsets P and Q. The common influence join (CIJ) returns the pairs of points (p, q),p ∈ P, q ∈ Q, such that there exists a location in space, being closer to p than to any other point in P and at the same time closer to q than to any other point in Q. In contrast to existing join operators between pointsets (i.e., e-distance joins and k-closest pairs), CIJ is parameter-free, providing a natural join result that finds application in marketing and decision support. We propose algorithms for the efficient evaluation of CIJ, for pointsets indexed by hierarchical multi-dimensional indexes. We validate the effectiveness and the efficiency of these methods via experimentation with synthetic and real spatial datasets. The experimental results show that a non-blocking algorithm, which computes intersecting pairs of Voronoi cells on-demand, is very efficient in practice, incurring only slightly higher I/O cost than the theoretical lower bound cost for the problem. © 2008 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/151927
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorMan, LTen_US
dc.contributor.authorMamoulis, Nen_US
dc.contributor.authorKarras, Pen_US
dc.date.accessioned2012-06-26T06:30:56Z-
dc.date.available2012-06-26T06:30:56Z-
dc.date.issued2008en_US
dc.identifier.citationProceedings - International Conference On Data Engineering, 2008, p. 100-109en_US
dc.identifier.issn1084-4627en_US
dc.identifier.urihttp://hdl.handle.net/10722/151927-
dc.description.abstractWe identify and formalize a novel join operator for two spatial pointsets P and Q. The common influence join (CIJ) returns the pairs of points (p, q),p ∈ P, q ∈ Q, such that there exists a location in space, being closer to p than to any other point in P and at the same time closer to q than to any other point in Q. In contrast to existing join operators between pointsets (i.e., e-distance joins and k-closest pairs), CIJ is parameter-free, providing a natural join result that finds application in marketing and decision support. We propose algorithms for the efficient evaluation of CIJ, for pointsets indexed by hierarchical multi-dimensional indexes. We validate the effectiveness and the efficiency of these methods via experimentation with synthetic and real spatial datasets. The experimental results show that a non-blocking algorithm, which computes intersecting pairs of Voronoi cells on-demand, is very efficient in practice, incurring only slightly higher I/O cost than the theoretical lower bound cost for the problem. © 2008 IEEE.en_US
dc.languageengen_US
dc.relation.ispartofProceedings - International Conference on Data Engineeringen_US
dc.titleCommon influence join: A natural join operation for spatial pointsetsen_US
dc.typeConference_Paperen_US
dc.identifier.emailMamoulis, N:nikos@cs.hku.hken_US
dc.identifier.authorityMamoulis, N=rp00155en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1109/ICDE.2008.4497418en_US
dc.identifier.scopuseid_2-s2.0-52649100453en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-52649100453&selection=ref&src=s&origin=recordpageen_US
dc.identifier.spage100en_US
dc.identifier.epage109en_US
dc.publisher.placeUnited Statesen_US
dc.identifier.scopusauthoridMan, LT=16032624200en_US
dc.identifier.scopusauthoridMamoulis, N=6701782749en_US
dc.identifier.scopusauthoridKarras, P=14028488200en_US
dc.identifier.citeulike4173434-

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