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Conference Paper: Reverse-nearest neighbor queries on uncertain moving object trajectories

TitleReverse-nearest neighbor queries on uncertain moving object trajectories
Authors
Issue Date2014
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 19th International Conference on Database Systems for Advanced Applications (DASFAA 2014), Bali, Indonesia, 21-24 April 2014. In Lecture Notes in Computer Science, 2014, v. 8422, p. 92-107 How to Cite?
AbstractReverse nearest neighbor (RNN) queries in spatial and spatio-temporal databases have received significant attention in the database research community over the last decade. A reverse nearest neighbor (RNN) query finds the objects having a given query object as its nearest neighbor. RNN queries find applications in data mining, marketing analysis, and decision making. Most previous research on RNN queries over trajectory databases assume that the data are certain. In realistic scenarios, however, trajectories are inherently uncertain due to measurement errors or time-discretized sampling. In this paper, we study RNN queries in databases of uncertain trajectories. We propose two types of RNN queries based on a well established model for uncertain spatial temporal data based on stochastic processes, namely the Markov model. To the best of our knowledge our work is the first to consider RNN queries on uncertain trajectory databases in accordance with the possible worlds semantics. We include an extensive experimental evaluation on both real and synthetic data sets to verify our theoretical results.
Persistent Identifierhttp://hdl.handle.net/10722/199309
ISBN
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252

 

DC FieldValueLanguage
dc.contributor.authorEmrich, Ten_US
dc.contributor.authorKriegel, HPen_US
dc.contributor.authorMamoulis, Nen_US
dc.contributor.authorNiedermayer, Jen_US
dc.contributor.authorRenz, Men_US
dc.contributor.authorZuefle, Aen_US
dc.date.accessioned2014-07-22T01:13:04Z-
dc.date.available2014-07-22T01:13:04Z-
dc.date.issued2014en_US
dc.identifier.citationThe 19th International Conference on Database Systems for Advanced Applications (DASFAA 2014), Bali, Indonesia, 21-24 April 2014. In Lecture Notes in Computer Science, 2014, v. 8422, p. 92-107en_US
dc.identifier.isbn978-3-319-05812-2-
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/10722/199309-
dc.description.abstractReverse nearest neighbor (RNN) queries in spatial and spatio-temporal databases have received significant attention in the database research community over the last decade. A reverse nearest neighbor (RNN) query finds the objects having a given query object as its nearest neighbor. RNN queries find applications in data mining, marketing analysis, and decision making. Most previous research on RNN queries over trajectory databases assume that the data are certain. In realistic scenarios, however, trajectories are inherently uncertain due to measurement errors or time-discretized sampling. In this paper, we study RNN queries in databases of uncertain trajectories. We propose two types of RNN queries based on a well established model for uncertain spatial temporal data based on stochastic processes, namely the Markov model. To the best of our knowledge our work is the first to consider RNN queries on uncertain trajectory databases in accordance with the possible worlds semantics. We include an extensive experimental evaluation on both real and synthetic data sets to verify our theoretical results.en_US
dc.languageengen_US
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.rightsThe original publication is available at www.springerlink.comen_US
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleReverse-nearest neighbor queries on uncertain moving object trajectoriesen_US
dc.typeConference_Paperen_US
dc.identifier.emailMamoulis, N: nikos@cs.hku.hken_US
dc.identifier.authorityMamoulis, N=rp00155en_US
dc.description.naturepostprinten_US
dc.identifier.doi10.1007/978-3-319-05813-9_7en_US
dc.identifier.scopuseid_2-s2.0-84900336012-
dc.identifier.hkuros230461en_US
dc.identifier.volume8422en_US
dc.identifier.spage92en_US
dc.identifier.epage107en_US
dc.publisher.placeGermanyen_US
dc.customcontrol.immutablesml 150401-

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