Perceived video quality evaluation based on interactive/repulsive relation between the QoE IFs

The user satisfaction measurement has gained high attention from Network Operators (NOs) and Service Providers (SPs) because their businesses are highly dependent on the user's satisfaction. Generally, the traditional strategies to measure the user's perception are based on Quality of Service (QoS), which is not sufficient to reflect the real user's perceived quality. Therefore, NOs and SPs start to develop new strategies based on the Quality of Experience (QoE) metric to analyze the relationship between the user's satisfaction and influence factors (QoE IFs). In this paper, a new method to build a predictive model to estimate user's satisfaction in terms of Mean Opinion Score (MOS) is proposed. The proposed method uses the dataset collected using the controlled testbed based on the YouTube video service. In the proposed model, the correlation matrix is used to develop a new heuristic method that used back-jumping technique to select the most beneficial factors to predict the optimal user's satisfaction.