Quality of Experience (QoE) is a metric that quantifies the quality experienced while using a service. This is a subjective metric that is crucial for determining the level of satisfaction with the quality of services, such as multimedia streaming or games. Because of its subjective character, QoE is estimated accurately by executing complex and cumbersome subjective studies, or not as accurately by using objective signal distortion metrics. In order to get the accuracy of the subjective approach and the practicality of the objective, we propose a method for estimation of QoE based on continuous user feedback using Online Learning techniques. This method provides for means to build accurate prediction models while circumventing the requirement for subjective studies.
|Title of host publication||Informal proceedings of the 19th Annual Machine Learning Conference of Belgium and The Netherlands (Benelearn'10, Leuven, Belgium, May 27-28, 2010)|
|Publication status||Published - 2010|
|Event||conference; Machine learning conference; 2010-05-27; 2010-05-28 - |
Duration: 27 May 2010 → 28 May 2010
|Conference||conference; Machine learning conference; 2010-05-27; 2010-05-28|
|Period||27/05/10 → 28/05/10|
|Other||Machine learning conference|