A mobile streaming media user quality of experience qoe correction method and server

Abstract

Disclosed are a correction method for the quality of experience (QoE) of a mobile streaming media user, and a server. The method comprises: receiving user behaviour data and current video damage data; according to the user behaviour data, obtaining a value of influence on the QoE of an individual; according to the current video damage data, obtaining initial user quality of experience QoEinit; and according to the value of influence on the QoE of the individual and the initial user quality of experience QoEinit, obtaining corrected individual user quality of experience QoEfinal.

Description

technical field [0001] The invention relates to the evaluation and management of user quality of experience in the field of wireless network communication, in particular to a method for modifying mobile streaming media user quality of experience QoE. Background technique [0002] With the continuous development of mobile communication technology, the demand for mobile streaming media services is growing explosively, and the importance of its performance evaluation is becoming increasingly prominent. [0003] Quality of Experience (QoE) is an end-to-end user concept. It measures the pros and cons of services from the user's perspective, and is the user's comprehensive subjective experience of the current network, service quality, and performance. The development of HTTP Streaming technology is to improve user service experience. Therefore, user quality of experience (QoE) is a core indicator for measuring the performance of HTTP streaming media services. [0004] The streami...

AI Technical Summary

Problems solved by technology

We can see that the existing evaluations only consider some factors that affect QoE, some only perform a single QoS and QoE mapping, and some directly simplify QoE into the state of the buffer

In the process of watching movies, the user will produce a series of operation behaviors such as pausing, changing the resolution, and exiting. Some of these behaviors may have a certain impact on the quality of the streaming media service, and some may express certain psychological states of the user. However, the existing evaluation methods often idealize the scene, assume that the network conditions remain unchanged, and ignore the impact of the user's operation behavior on the streaming media service quality during the viewing process, which has a large deviation from the user's actual use environment, so the final The evaluation results are likely to be inconsistent with the actual user experience quality

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