QoE Prediction for IPTV Based on Imbalanced Dataset by the PNN-PSO algorithm
Xin Wei, Mengwen Diao, Hu Zhengying, Xiao Hu, Yun Gao, Ruochen Huang · 2018
User Quality of Experience (QoE) has been brought to service providers' attention with the boom of multimedia services, such as Internet Protocol Television (IPTV). In this paper, we propose a QoE prediction model based on improved probabilistic neural network (PNN) to study the mapping relationship between IPTV viewing records and the user QoE. Specifically, we combine the particle swarm optimization (PSO) with PNN, utilizing PSO to search the spread parameter in PNN, thus this parameter can be automatically obtained, saving much time and effort. Experimental results show that the PNN-PSO can achieve the highest G-mean in comparison with other models. Moreover, it finds the best spread automatically and consequently increases prediction accuracy by 13% compared with the PNN.