Multi-layer neural network based user QoE (Quality of Experience) prediction method in video service

Abstract

The invention discloses a multi-layer neural network based user QoE prediction method in a video service. Data is preprocessed by selecting characteristic parameters that influence user experience from the video service, and mapping the characteristic parameters into user QoE according to fault report or non fault report of the user; a QoE prediction model of the multi-layer neural network is established, and the neural network comprises an input layer, a first hidden layer, a second hidden layer, a third hidden layer and an output layer successively from bottom to top; the preprocessed data is input, an optimal parameter value of the model is obtained, and the established neural network model is trained; and user QoE prediction is completed; According to the invention, the data is preprocessed, important characteristic attributes are selected, different types of parameters are considered in an integrated way, the video quality predicted by the model approaches the subjective video quality experience of the user more, the user QoE can be predicted in a better way, results can be back fed timely and accurately, and a service provider and a network service provider can complete the video service as well as transmission services continuously.

Description

technical field [0001] The invention relates to user experience quality prediction, in particular to a user experience quality prediction method based on a multi-layer neural network in video services. Background technique [0002] The rapid development of Internet technology enables people to access various multimedia services, and in particular, IPTV now provides various services, making people's lives colorful. But on the other hand, service providers and network operators are more concerned about the quality of the provided video services, that is, what is the IPTV user experience of watching videos. This makes the prediction and evaluation of user experience quality a hot spot that service providers and network operators pay attention to. Quality of Experience (QoE) is defined as "the overall acceptability of an application or service as perceived by the end user". QoE is not only affected by the service itself, but also by the user's environment. Because machine lea...

AI Technical Summary

Problems solved by technology

However, traditional machine learning methods, such as support vector machines and decision trees, have very limited predictive performance and cannot accurately complete this task. Therefore, it is necessary to design new models and predictive methods to complete the prediction and improvement of IPTV user experience quality

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