Measuring the Quality of Experience of Web users
Measuring the Quality of Experience of Web users
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DOI：
10.1145/3027947.3027949
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发表时间：
2016-08
期刊：
影响因子：
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通讯作者：
E. Bocchi;L. D. Cicco;D. Rossi
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文献类型：
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作者：
E. Bocchi;L. D. Cicco;D. Rossi
衡量Web用户体验质量（WebQoE）面临以下权衡。一方面，当前的实践是求助于度量标准，例如文档完成时间（onLoad），虽然知道不准确，但度量方法很简单。另一方面，还有一些参数，如b谷歌的SpeedIndex，能够更好地与实际用户体验相关联，但评估起来相当复杂，因此只能在实验室进行实验。在本文中，我们首先提供了WebQoE评估可用的度量和工具的综合技术状态。然后，我们将这些指标应用于代表性数据集（Alexa前100个网页），以更好地说明它们的相似性，差异性，优势和局限性。接下来，我们将引入受b谷歌的SpeedIndex启发的新指标，这些指标在计算复杂性方面提供了显著的优势，同时保持了与SpeedIndex的高度相关性。这些属性使得我们提出的度量具有高度的相关性和实用性。
Measuring quality of Web users experience (WebQoE) faces the following trade-off. On the one hand, current practice is to resort to metrics, such as the document completion time (onLoad), that are simple to measure though knowingly inaccurate. On the other hand, there are metrics, like Google’s SpeedIndex, that are better correlated with the actual user experience, but are quite complex to evaluate and, as such, relegated to lab experiments. In this paper, we first provide a comprehensive state of the art on the metrics and tools available for WebQoE assessment. We then apply these metrics to a representative dataset (the Alexa top-100 webpages) to better illustrate their similarities, differences, advantages, and limitations. We next introduce novel metrics, inspired by Google’s SpeedIndex, that offer significant advantage in terms of computational complexity, while maintaining a high correlation with the SpeedIndex. These properties make our proposed metrics highly relevant and of practical use.