利用基于网络实时数据来建立测量标准，从而窃取用户的情绪状况及喜好，这主意并没有多少新意，即使用它来预测人的行为也是一样。
The idea of tapping web-based data to build a real-time measure of users' emotions and preferences is not new. Nor is that of using the results to predict their behaviour.
建立一个可扩展的、通用的网络测量平台是全面了解大规模网络行为的基础。
Building a scalable and universal network measurement platform is the basis to understand synthetical behaviors of large-scale networks.
传统的业务流模型大多是基于泊松或贝努力过程的，而这些模型表现出的行为与实际网络的测量结果不符。
The conventional models are mostly based on Poisson model or Bernoulli process, but the activity of these models is not consistent with the measured results of the real networks.
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