García Torres, MiguelPinto Roa, Diego P.Núñez Castillo, CarlosQuiñonez, BrendaVázquez, GabrielaAllegretti, MauricioGarcía Díaz, María E.2024-03-012024-03-012024Computer Communications, vol. 217, p. 230-24510.1016/j.comcom.2024.02.004https://hdl.handle.net/10433/20268Proyectos de investigación PID2020- 117954RB-C21 PY20-00870 UPO-138516 PINV15-0257Nowadays, mobile service providers perceive the user experience as a reliable indicator of the quality associated to a service. Given a set of Quality of Service (QoS) factors, the aim is to predict the Quality of Experience (QoE), measured in terms of the Mean Opinion Score (MOS). Although this problem is receiving much attention, there are still some challenges that require more research in order to find effective solutions for meeting user’s expectation in terms of service quality. A core challenge in this topic refers to the analysis of the contribution of each factor to the QoS/QoE Model. In this work, we study the mapping between QoS and QoE on video and web-based services using a machine learning approach. For such purpose, we design a lab-testing methodology to emulate different cellular transmission network scenarios. Then, we address the problem of inducing a predictive model and identifying relevant QoS factors. Results suggest that bandwidth is a key factor when analyzing user’s perception of service quality.application/pdfenAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Ordinal classificationFeature selectionQuality of serviceQuality of experienceMean opinion scorejournal articleopen access