QoE Prediction for IPTV Based on Imbalanced Dataset by the PNN-PSO algorithm | IEEE Conference Publication | IEEE Xplore

QoE Prediction for IPTV Based on Imbalanced Dataset by the PNN-PSO algorithm


Abstract:

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 th...Show More

Abstract:

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.
Date of Conference: 25-29 June 2018
Date Added to IEEE Xplore: 30 August 2018
ISBN Information:
Electronic ISSN: 2376-6506
Conference Location: Limassol, Cyprus

References

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