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Conference Paper: Efficient top-k spatial distance joins

TitleEfficient top-k spatial distance joins
Authors
KeywordsAggregate function
Alternative solutions
Spatial distance
Spatial objects
Issue Date2013
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 13th International Symposium on Spatial and Temporal Databases (SSTD 2013), Munich; Germany, 21-23 August 2013. In Lecture Notes in Computer Science, 2013, v. 8098, p. 1-18 How to Cite?
AbstractConsider two sets of spatial objects R and S, where each object is assigned a score (e.g., ranking). Given a spatial distance threshold ε and an integer k, the top-k spatial distance join (k- SDJ) returns the k pairs of objects, which have the highest combined score (based on an aggregate function γ) among all object pairs in R x S which have spatial distance at most ε. Despite the practical application value of this query, it has not received adequate attention in the past. In this paper, we fill this gap by proposing methods that utilize both location and score information from the objects, enabling top-k join computation by accessing a limited number of objects. Extensive experiments demonstrate that a technique which accesses blocks of data from R and S ordered by the object scores and then joins them using an aR-tree based module performs best in practice and outperforms alternative solutions by a wide margin. © 2013 Springer-Verlag.
DescriptionConference Theme: Advances in Spatial and Temporal Databases
LNCS v. 8098 entitled: Advances in spatial and temporal databases : 13th International Symposium, SSTD 2013 ... proceedings Embargo till 2014-Aug-01
Persistent Identifierhttp://hdl.handle.net/10722/189620
ISBN
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252

 

DC FieldValueLanguage
dc.contributor.authorQi, Sen_US
dc.contributor.authorBouros, Pen_US
dc.contributor.authorMamoulis, Nen_US
dc.date.accessioned2013-09-17T14:50:22Z-
dc.date.available2013-09-17T14:50:22Z-
dc.date.issued2013en_US
dc.identifier.citationThe 13th International Symposium on Spatial and Temporal Databases (SSTD 2013), Munich; Germany, 21-23 August 2013. In Lecture Notes in Computer Science, 2013, v. 8098, p. 1-18en_US
dc.identifier.isbn978-364240234-0-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/189620-
dc.descriptionConference Theme: Advances in Spatial and Temporal Databases-
dc.descriptionLNCS v. 8098 entitled: Advances in spatial and temporal databases : 13th International Symposium, SSTD 2013 ... proceedings Embargo till 2014-Aug-01-
dc.description.abstractConsider two sets of spatial objects R and S, where each object is assigned a score (e.g., ranking). Given a spatial distance threshold ε and an integer k, the top-k spatial distance join (k- SDJ) returns the k pairs of objects, which have the highest combined score (based on an aggregate function γ) among all object pairs in R x S which have spatial distance at most ε. Despite the practical application value of this query, it has not received adequate attention in the past. In this paper, we fill this gap by proposing methods that utilize both location and score information from the objects, enabling top-k join computation by accessing a limited number of objects. Extensive experiments demonstrate that a technique which accesses blocks of data from R and S ordered by the object scores and then joins them using an aR-tree based module performs best in practice and outperforms alternative solutions by a wide margin. © 2013 Springer-Verlag.-
dc.languageengen_US
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/-
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.rightsThe original publication is available at www.springerlink.com-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectAggregate function-
dc.subjectAlternative solutions-
dc.subjectSpatial distance-
dc.subjectSpatial objects-
dc.titleEfficient top-k spatial distance joinsen_US
dc.typeConference_Paperen_US
dc.identifier.emailQi, S: syqi2@cs.hku.hken_US
dc.identifier.emailBouros, P: pbouros@hku.hken_US
dc.identifier.emailMamoulis, N: nikos@cs.hku.hk-
dc.identifier.authorityMamoulis, N=rp00155en_US
dc.description.naturepostprint-
dc.identifier.doi10.1007/978-3-642-40235-7_1-
dc.identifier.scopuseid_2-s2.0-84881218196-
dc.identifier.hkuros221073en_US
dc.identifier.volume8098-
dc.identifier.spage1en_US
dc.identifier.epage18en_US
dc.publisher.placeGermany-
dc.customcontrol.immutablesml 140117-

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