File Download
  Links for fulltext
     (May Require Subscription)
Supplementary

Conference Paper: Efficient point-based trajectory search

TitleEfficient point-based trajectory search
Authors
Issue Date2015
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 14th International on Symposium on Spatial and Temporal Databases (SSTD 2015), Hong Kong, China, 26-28 August 2015. In Lecture Notes in Computer Science, 2015, v. 9239, p. 179-196 How to Cite?
AbstractTrajectory data capture the traveling history of moving objects such as people or vehicles. With the proliferation of GPS and tracking technology, huge volumes of trajectories are rapidly generated and collected. Under this, applications such as route recommendation and traveling behavior mining call for efficient trajectory retrieval. In this paper, we first focus on distance-based trajectory search; given a collection of trajectories and a set query points, the goal is to retrieve the top-k trajectories that pass as close as possible to all query points. We advance the state-of-the-art by combining existing approaches to a hybrid method and also proposing an alternative, more efficient rangebased approach. Second, we propose and study the practical variant of bounded distance-based search, which takes into account the temporal characteristics of the searched trajectories. Through an extensive experimental analysis with real trajectory data, we show that our rangebased approach outperforms previous methods by at least one order of magnitude. © Springer International Publishing Switzerland 2015.
DescriptionLNCS v. 9239 entitled: Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. Proceedings
Persistent Identifierhttp://hdl.handle.net/10722/229720
ISBN
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252

 

DC FieldValueLanguage
dc.contributor.authorQi, S-
dc.contributor.authorBouros, P-
dc.contributor.authorSacharidis, D-
dc.contributor.authorMamoulis, N-
dc.date.accessioned2016-08-23T14:12:52Z-
dc.date.available2016-08-23T14:12:52Z-
dc.date.issued2015-
dc.identifier.citationThe 14th International on Symposium on Spatial and Temporal Databases (SSTD 2015), Hong Kong, China, 26-28 August 2015. In Lecture Notes in Computer Science, 2015, v. 9239, p. 179-196-
dc.identifier.isbn978-3-319-22362-9-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/229720-
dc.descriptionLNCS v. 9239 entitled: Advances in Spatial and Temporal Databases: 14th International Symposium, SSTD 2015, Hong Kong, China, August 26-28, 2015. Proceedings-
dc.description.abstractTrajectory data capture the traveling history of moving objects such as people or vehicles. With the proliferation of GPS and tracking technology, huge volumes of trajectories are rapidly generated and collected. Under this, applications such as route recommendation and traveling behavior mining call for efficient trajectory retrieval. In this paper, we first focus on distance-based trajectory search; given a collection of trajectories and a set query points, the goal is to retrieve the top-k trajectories that pass as close as possible to all query points. We advance the state-of-the-art by combining existing approaches to a hybrid method and also proposing an alternative, more efficient rangebased approach. Second, we propose and study the practical variant of bounded distance-based search, which takes into account the temporal characteristics of the searched trajectories. Through an extensive experimental analysis with real trajectory data, we show that our rangebased approach outperforms previous methods by at least one order of magnitude. © Springer International Publishing Switzerland 2015.-
dc.languageeng-
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/-
dc.relation.ispartofLecture Notes in Computer Science-
dc.rightsThe final publication is available at Springer via http://dx.doi.org/[insert DOI]-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.titleEfficient point-based trajectory search-
dc.typeConference_Paper-
dc.identifier.emailMamoulis, N: nikos@cs.hku.hk-
dc.identifier.authorityMamoulis, N=rp00155-
dc.description.naturepostprint-
dc.identifier.doi10.1007/978-3-319-22363-6_10-
dc.identifier.scopuseid_2-s2.0-84983770595-
dc.identifier.hkuros262971-
dc.identifier.volume9239-
dc.identifier.spage179-
dc.identifier.epage196-
dc.publisher.placeGermany-
dc.customcontrol.immutablesml 160915-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats