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dc.contributor.authorBejarano Luque, Juan Luis
dc.contributor.authorToril-Genoves, Matias 
dc.contributor.authorFernández-Navarro, Mariano 
dc.contributor.authorJiménez, Luis R.
dc.contributor.authorLuna-Ramírez, Salvador 
dc.date.accessioned2021-10-01T17:02:46Z
dc.date.available2021-10-01T17:02:46Z
dc.date.created2021-09
dc.date.issued2021-09
dc.identifier.urihttps://hdl.handle.net/10630/22934
dc.description.abstractIn spite of the vast set of measurements provided by current mobile networks, cellular operators have problems to pinpoint problematic locations because the origin of such measurements (i.e., user location) is usually not registered. At the same time, social networks generate a huge amount of data that can be used to infer population density. In this work, a data-driven model is proposed to deduce the statistical distribution of connections, exploiting the knowledge of network layout and population density in the sceario. Due to the absence of GPS measurements, the proposed method combines data from radio connection traces stored in the network management system and geolocated posts from social networks. This information is enriched with user context information inferred from their traffic attributes. The method is tested with a large trace dataset from a live Long Term Evolution (LTE) network and a database of geotagged messages from two social networks (Twitter and Flickr).es_ES
dc.description.sponsorshipUniversidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.es_ES
dc.language.isoenges_ES
dc.rightsinfo:eu-repo/semantics/openAccesses_ES
dc.subjectRedes socialeses_ES
dc.subject.otherPosicionamientoes_ES
dc.subject.otherRedes socialeses_ES
dc.subject.otherBig dataes_ES
dc.subject.otherData mininges_ES
dc.subject.otherLTEes_ES
dc.titleStatistical model for mobile user positioning based on social information.es_ES
dc.typeinfo:eu-repo/semantics/conferenceObjectes_ES
dc.centroE.T.S.I. Telecomunicaciónes_ES
dc.relation.eventtitle3rd Post-IRACON Meetinges_ES
dc.relation.eventplaceOnlinees_ES
dc.relation.eventdateMayo 2021es_ES


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