流媒体视频质量评估的混合上下文用户感知模型

M. Diallo, N. Maréchal, H. Afifi
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引用次数: 8

摘要

用户满意度是服务提供商减少流失、推广新服务和提高ARPU(每用户平均收益)的目标。本文提出了一种新的混合评估技术。它改进了已知的数学模型,使用上下文信息和主观测试进行质量评估。然后用内容特征、设备类型和网络状态等新特征丰富该模型,并将其与现有技术进行比较。本文还分析了应用程序参数(启动时间和缓冲比率)对用户感知质量的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Hybrid Contextual User Perception Model for Streamed Video Quality Assessment
Users' satisfaction is the service providers' aim to reduce the churn, promote new services and improve ARPU (Average Revenue per User). In this work, a novel hybrid assessment technique is presented. It refines known mathematical models for quality assessment using both context information and subjectives tests. The model is then enriched with new features such as content characteristics, device type and network status, and compared to the state of the art. The effect of application parameters (startup time and buffering ratio) on user perceived quality is also analyzed in this article.
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