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Conference Paper: Querying uncertain spatio-temporal data

TitleQuerying uncertain spatio-temporal data
Authors
KeywordsAnswering queries
Experimental evaluation
Matrix multiplication
Object location
Object trajectories
Issue Date2012
PublisherIEEE Computer Society.
Citation
The 28th IEEE International Conference on Data Engineering (ICDE 2012), Washington, DC., 1-5 April 2012. In International Conference on Data Engineering Proceedings, 2012, p. 354-365 How to Cite?
AbstractThe problem of modeling and managing uncertain data has received a great deal of interest, due to its manifold applications in spatial, temporal, multimedia and sensor databases. There exists a wide range of work covering spatial uncertainty in the static (snapshot) case, where only one point of time is considered. In contrast, the problem of modeling and querying uncertain spatio-temporal data has only been treated as a simple extension of the spatial case, disregarding time dependencies between consecutive timestamps. In this work, we present a framework for efficiently modeling and querying uncertain spatio-temporal data. The key idea of our approach is to model possible object trajectories by stochastic processes. This approach has three major advantages over previous work. First it allows answering queries in accordance with the possible worlds model. Second, dependencies between object locations at consecutive points in time are taken into account. And third it is possible to reduce all queries on this model to simple matrix multiplications. Based on these concepts we propose efficient solutions for different probabilistic spatio-temporal queries. In an experimental evaluation we show that our approaches are several order of magnitudes faster than state-of-the-art competitors. © 2012 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/164919
ISSN
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorEmrich, Ten_US
dc.contributor.authorKriegel, HPen_US
dc.contributor.authorMamoulis, Nen_US
dc.contributor.authorRenz, Men_US
dc.contributor.authorZuefle, Aen_US
dc.date.accessioned2012-09-20T08:12:24Z-
dc.date.available2012-09-20T08:12:24Z-
dc.date.issued2012en_US
dc.identifier.citationThe 28th IEEE International Conference on Data Engineering (ICDE 2012), Washington, DC., 1-5 April 2012. In International Conference on Data Engineering Proceedings, 2012, p. 354-365en_US
dc.identifier.issn1084-4627-
dc.identifier.urihttp://hdl.handle.net/10722/164919-
dc.description.abstractThe problem of modeling and managing uncertain data has received a great deal of interest, due to its manifold applications in spatial, temporal, multimedia and sensor databases. There exists a wide range of work covering spatial uncertainty in the static (snapshot) case, where only one point of time is considered. In contrast, the problem of modeling and querying uncertain spatio-temporal data has only been treated as a simple extension of the spatial case, disregarding time dependencies between consecutive timestamps. In this work, we present a framework for efficiently modeling and querying uncertain spatio-temporal data. The key idea of our approach is to model possible object trajectories by stochastic processes. This approach has three major advantages over previous work. First it allows answering queries in accordance with the possible worlds model. Second, dependencies between object locations at consecutive points in time are taken into account. And third it is possible to reduce all queries on this model to simple matrix multiplications. Based on these concepts we propose efficient solutions for different probabilistic spatio-temporal queries. In an experimental evaluation we show that our approaches are several order of magnitudes faster than state-of-the-art competitors. © 2012 IEEE.-
dc.languageengen_US
dc.publisherIEEE Computer Society.-
dc.relation.ispartofInternational Conference on Data Engineering Proceedingsen_US
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectAnswering queries-
dc.subjectExperimental evaluation-
dc.subjectMatrix multiplication-
dc.subjectObject location-
dc.subjectObject trajectories-
dc.titleQuerying uncertain spatio-temporal dataen_US
dc.typeConference_Paperen_US
dc.identifier.emailEmrich, T: emrich@dbs.ifi.lmu.deen_US
dc.identifier.emailKriegel, HP: kriegel@dbs.ifi.lmu.de-
dc.identifier.emailMamoulis, N: nikos@cs.hku.hk-
dc.identifier.emailRenz, M: renz@dbs.ifi.lmu.de-
dc.identifier.emailZuefle, A: zuefle@dbs.ifi.lmu.de-
dc.identifier.authorityMamoulis, N=rp00155en_US
dc.description.naturepublished_or_final_version-
dc.identifier.doi10.1109/ICDE.2012.94-
dc.identifier.scopuseid_2-s2.0-84864270945-
dc.identifier.hkuros208283en_US
dc.identifier.spage354-
dc.identifier.epage365-
dc.identifier.isiWOS:000309122100034-
dc.publisher.placeUnited States-
dc.customcontrol.immutablesml 130402-

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