RT Journal Article
T1 Feature Selection applied to QoS/QoE Modeling on video and web-based Mobile data Services: An ordinal approach
A1 García Torres, Miguel
A1 Pinto Roa, Diego P.
A1 Núñez Castillo, Carlos
A1 Quiñonez, Brenda
A1 Vázquez, Gabriela
A1 Allegretti, Mauricio
A1 García Díaz, María E.
K1 Ordinal classification
K1 Feature selection
K1 Quality of service
K1 Quality of experience
K1 Mean opinion score
AB Nowadays, 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.
PB Elsevier
YR 2024
FD 2024
LK https://hdl.handle.net/10433/20268
UL https://hdl.handle.net/10433/20268
LA en
NO Computer Communications, vol. 217, p. 230-245
NO Proyectos de investigaciónPID2020- 117954RB-C21PY20-00870UPO-138516PINV15-0257
NO Universidad Pablo de Olavide. Departamento de Deporte e Informática
DS RIO
RD May 24, 2026