Show simple item record

dc.contributor.authorMesquita, Jorge
dc.contributor.authorOsorio, Guillermo
dc.contributor.authorGarcía-Diaz, María
dc.contributor.authorGarcía Torres, Miguel
dc.contributor.authorPinto Roa, Diego Pedro 
dc.contributor.authorNúñez Castillo, Carlos Heriberto 
dc.contributor.otherUniversidad Nacional de Asunción - Facultad Politécnicaes
dc.date.accessioned2022-04-27T23:41:52Z
dc.date.available2022-04-27T23:41:52Z
dc.date.issued2019
dc.identifier.urihttp://hdl.handle.net/20.500.14066/3733
dc.description.abstractQuality of experience (QoE) can be defined as the overall level of acceptability of an application or service, as perceived by the end-user. The perceived QoE of mobile user plays a key role in the business of the telecom carriers. This work has focused in design a model capable of predicting the QoE of the end-user using a number of Machine Learning approaches, based on quality of service (QoS) metrics from different sources like the mobile device, the mobile network and also subjective metrics given by the user (QoE and Mood surveys) in a real life setup. An android app, a metric collection platform, a system for data processing and semi-automatic analysis of metrics has been developed as a part of this work. The experimental results show that by assembling a combined model of the algorithms with best observed individual performance, improvements in the overall performance of the prediction can be achieved.es
dc.description.sponsorshipCONACYT – Consejo Nacional de Ciencia y Tecnologíaes
dc.language.isoenges
dc.subject.classification4 Transporte, telecomunicaciones y otras infraestructurases
dc.subject.otherQOEes
dc.subject.otherQOSes
dc.subject.otherMACHINE LEARNINGes
dc.subject.otherENSSEMBLED ALGORITHMSes
dc.subject.otherANDROID APPes
dc.titleQoE estimation in mobile networks using machine learninges
dc.typeresearch articlees
dc.conference.date2019-03
dc.conference.placeGeorgia, USes
dc.conference.titleConference of Computational Interdisciplinary Science (CCIS 2019)es
dc.description.fundingtextPROCIENCIAes
dc.relation.projectCONACYTPINV15-257es
dc.rights.accessRightsopen accesses
dc.subject.ocdeCOMPUTACIONes


Files in this item

This item appears in the following Collection(s)

  • Artículos científicos
    La colección comprende artículos científicos, revisiones y artículos de conferencia que son resultados de actividades de I+D financiadas por el Programa PROCIENCIA.

Show simple item record