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Analysis of location prediction performance of LZ algorithms using GSM Cell-based location data

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dc.affiliation.dptoUC3M. Departamento de Ingeniería Telemáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Aplicaciones y Servicios Telemáticos (GAST)es
dc.contributor.authorRodriguez-Carrión, Alicia
dc.contributor.authorGarcía Rubio, Carlos
dc.contributor.authorCampo Vázquez, María Celeste
dc.contributor.authorCortés Martín, Alberto
dc.contributor.authorGarcía Lozano, Estrella María
dc.contributor.authorNoriega-Vivas, Patricia
dc.date.accessioned2012-01-27T14:08:43Z
dc.date.available2012-01-27T14:08:43Z
dc.date.issued2011
dc.descriptionProceedings of the 5th International Symposium of Ubiquitous Computing and Ambient Intelligence (UCAMI 2011), December 5-8th, 2011, Riviera Maya, Mexicoen
dc.description.abstractPredictions about users' next locations allow bringing forward their future context, thus having additional time to react. To make such predictions, algorithms capable of learning mobility patterns and estimating the next location are needed. This work is focused on making the predictions on mobile terminals, thus resource consumption being an important constraint. Among the predictors with low resource consumption, the family of LZ algorithms has been chosen to study their performance, analyzing the results drawn from processing location records of 95 users. The main contribution is to divide the algorithms into two phases, thus being possible to use the best combination to obtain better prediction accuracy or lower resource consumption.en
dc.description.sponsorshipProyecto CCG10-UC3M/TIC-4992 de la Comunidad Autónoma de Madrid y la Universidad Carlos III de Madrides
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/10016/13103
dc.language.isoeng
dc.publisherUCAMI
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.ecienciaTelecomunicacioneses
dc.subject.otherPredictionen
dc.subject.otherLZen
dc.titleAnalysis of location prediction performance of LZ algorithms using GSM Cell-based location dataen
dc.typeconference output*
dc.type.hasVersionAM*
dspace.entity.typePublication
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