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Conference Paper: Probabilistic spatial queries on existentially uncertain data

TitleProbabilistic spatial queries on existentially uncertain data
Authors
Issue Date2005
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
Lecture Notes In Computer Science, 2005, v. 3633, p. 400-417 How to Cite?
AbstractWe study the problem of answering spatial queries in databases where objects exist with some uncertainty and they are associated with an existential probability. The goal of a thresholding probabilistic spatial query is to retrieve the objects that qualify the spatial predicates with probability that exceeds a threshold. Accordingly, a ranking probabilistic spatial query selects the objects with the highest probabilities to qualify the spatial predicates. We propose adaptations of spatial access methods and search algorithms for probabilistic versions of range queries and nearest neighbors and conduct an extensive experimental study, which evaluates the effectiveness of proposed solutions. © Springer-Verlag Berlin Heidelberg 2005.
Persistent Identifierhttp://hdl.handle.net/10722/93400
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252
References

 

DC FieldValueLanguage
dc.contributor.authorDai, Xen_HK
dc.contributor.authorYiu, MLen_HK
dc.contributor.authorMamoulis, Nen_HK
dc.contributor.authorTao, Yen_HK
dc.contributor.authorVaitis, Men_HK
dc.date.accessioned2010-09-25T14:59:56Z-
dc.date.available2010-09-25T14:59:56Z-
dc.date.issued2005en_HK
dc.identifier.citationLecture Notes In Computer Science, 2005, v. 3633, p. 400-417en_HK
dc.identifier.issn0302-9743en_HK
dc.identifier.urihttp://hdl.handle.net/10722/93400-
dc.description.abstractWe study the problem of answering spatial queries in databases where objects exist with some uncertainty and they are associated with an existential probability. The goal of a thresholding probabilistic spatial query is to retrieve the objects that qualify the spatial predicates with probability that exceeds a threshold. Accordingly, a ranking probabilistic spatial query selects the objects with the highest probabilities to qualify the spatial predicates. We propose adaptations of spatial access methods and search algorithms for probabilistic versions of range queries and nearest neighbors and conduct an extensive experimental study, which evaluates the effectiveness of proposed solutions. © Springer-Verlag Berlin Heidelberg 2005.en_HK
dc.languageengen_HK
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_HK
dc.relation.ispartofLecture Notes in Computer Scienceen_HK
dc.titleProbabilistic spatial queries on existentially uncertain dataen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailMamoulis, N:nikos@cs.hku.hken_HK
dc.identifier.authorityMamoulis, N=rp00155en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-26444512067en_HK
dc.identifier.hkuros103342en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-26444512067&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume3633en_HK
dc.identifier.spage400en_HK
dc.identifier.epage417en_HK
dc.publisher.placeGermanyen_HK
dc.identifier.scopusauthoridDai, X=8889338400en_HK
dc.identifier.scopusauthoridYiu, ML=8589889600en_HK
dc.identifier.scopusauthoridMamoulis, N=6701782749en_HK
dc.identifier.scopusauthoridTao, Y=7402420191en_HK
dc.identifier.scopusauthoridVaitis, M=16240387400en_HK

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