论文标题
重建网络
Reconstructing networks
论文作者
论文摘要
复杂的网络数据集通常带有缺少信息的问题：尚未测量或发现的交互数据可能会受到错误的影响，或者由于隐私问题而被隐藏。该元素概述了解决此问题的想法，方法和技术，并共同定义了网络重建领域。考虑到主题的程度，我们将重点关注植根于统计物理和信息理论的推论方法。讨论将根据重建任务的不同量表进行组织，即是重建网络的宏观结构，推断其中尺度属性还是预测单个显微镜连接。
Complex networks datasets often come with the problem of missing information: interactions data that have not been measured or discovered, may be affected by errors, or are simply hidden because of privacy issues. This Element provides an overview of the ideas, methods and techniques to deal with this problem and that together define the field of network reconstruction. Given the extent of the subject, we shall focus on the inference methods rooted in statistical physics and information theory. The discussion will be organized according to the different scales of the reconstruction task, that is, whether the goal is to reconstruct the macroscopic structure of the network, to infer its mesoscale properties, or to predict the individual microscopic connections.
