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Conference Paper: Evaluating trajectory queries over imprecise location data

TitleEvaluating trajectory queries over imprecise location data
Authors
KeywordsData uncertainty
Experimental studies
External environments
Imprecise data
Large database
Location data
Measuring device
Potential threats
Real data sets
Rescue operations
Issue Date2012
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 24th International Conference on Scientific and Statistical DatabaseManagement (SSDBM 2012), Chania, Crete, Greece, 25-27 June 2012. In Lecture Notes in Computer Science, 2012, v. 7338, p. 56-74 How to Cite?
AbstractTrajectory queries, which retrieve nearby objects for every point of a given route, can be used to identify alerts of potential threats along a vessel route, or monitor the adjacent rescuers to a travel path. However, the locations of these objects (e.g., threats, succours) may not be precisely obtained due to hardware limitations of measuring devices, as well as the constantly-changing nature of the external environment. Ignoring data uncertainty can render low query quality, and cause undesirable consequences such as missing alerts of threats and poor response time in rescue operations. Also, the query is quite time-consuming, since all the points on the trajectory are considered. In this paper, we study how to efficiently evaluate trajectory queries over imprecise location data, by proposing a new concept called the u-bisector. In general, the u-bisector is an extension of bisector to handle imprecise data. Based on the u-bisector, we design several novel filters to make our solution scalable to a long trajectory and a large database size. An extensive experimental study on real datasets suggests that our proposal produces better results than traditional solutions that do not consider data imprecision. © 2012 Springer-Verlag.
Persistent Identifierhttp://hdl.handle.net/10722/164908
ISBN
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252

 

DC FieldValueLanguage
dc.contributor.authorXie, Xen_US
dc.contributor.authorCheng, Ren_US
dc.contributor.authorYiu, MLen_US
dc.date.accessioned2012-09-20T08:12:20Z-
dc.date.available2012-09-20T08:12:20Z-
dc.date.issued2012en_US
dc.identifier.citationThe 24th International Conference on Scientific and Statistical DatabaseManagement (SSDBM 2012), Chania, Crete, Greece, 25-27 June 2012. In Lecture Notes in Computer Science, 2012, v. 7338, p. 56-74en_US
dc.identifier.isbn978-364231234-2-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/164908-
dc.description.abstractTrajectory queries, which retrieve nearby objects for every point of a given route, can be used to identify alerts of potential threats along a vessel route, or monitor the adjacent rescuers to a travel path. However, the locations of these objects (e.g., threats, succours) may not be precisely obtained due to hardware limitations of measuring devices, as well as the constantly-changing nature of the external environment. Ignoring data uncertainty can render low query quality, and cause undesirable consequences such as missing alerts of threats and poor response time in rescue operations. Also, the query is quite time-consuming, since all the points on the trajectory are considered. In this paper, we study how to efficiently evaluate trajectory queries over imprecise location data, by proposing a new concept called the u-bisector. In general, the u-bisector is an extension of bisector to handle imprecise data. Based on the u-bisector, we design several novel filters to make our solution scalable to a long trajectory and a large database size. An extensive experimental study on real datasets suggests that our proposal produces better results than traditional solutions that do not consider data imprecision. © 2012 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.subjectData uncertainty-
dc.subjectExperimental studies-
dc.subjectExternal environments-
dc.subjectImprecise data-
dc.subjectLarge database-
dc.subjectLocation data-
dc.subjectMeasuring device-
dc.subjectPotential threats-
dc.subjectReal data sets-
dc.subjectRescue operations-
dc.titleEvaluating trajectory queries over imprecise location dataen_US
dc.typeConference_Paperen_US
dc.identifier.emailCheng, R: ckcheng@cs.hku.hken_US
dc.identifier.authorityCheng, R=rp00074en_US
dc.identifier.doi10.1007/978-3-642-31235-9_4-
dc.identifier.scopuseid_2-s2.0-84863433694-
dc.identifier.hkuros206212en_US
dc.identifier.volume7338-
dc.identifier.spage56-
dc.identifier.epage74-
dc.publisher.placeGermany-
dc.customcontrol.immutablesml 130917-

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