On User-Centric Modular QoE Prediction for VoIP Based on Machine-Learning Algorithms

The impact of the network performance on the quality of experience (QoE) for various services is not well-understood. Assessing the impact of different network and channel conditions on the user experience is important for improving the telecommunication services. The QoE for various wireless servic...

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Veröffentlicht in:	IEEE transactions on mobile computing Jg. 15; H. 6; S. 1443 - 1456
Hauptverfasser:	Charonyktakis, Paulos, Plakia, Maria, Tsamardinos, Ioannis, Papadopouli, Maria
Format:	Magazine Article
Sprache:	Englisch
Veröffentlicht:	Los Alamitos IEEE 01.06.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithm design and analysis Algorithms Classifiers Estimation Loss measurement Modular Networks Neural networks Packets (communication) Prediction algorithms quality of experience Quality of service Telephones Training Voice VoIP VoIP (protocol) Wireless networks modeling PESQ VoIP wireless networks user-centric machine learning statistical analysis E-model quality of experience
ISSN:	1536-1233, 1558-0660
Online-Zugang:	Volltext
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