Temporal Scale of Dynamic Networks
Temporal Scale of Dynamic Networks
复制标题
动态网络的时间尺度
DOI：
10.1007/978-3-642-36461-7_4
复制
发表时间：
2013
期刊：
影响因子：
--
通讯作者：
T. Berger
中科院分区：
文献类型：
--
作者：
R. Caceres;T. Berger
无论是分子还是人的相互作用，本质上都是动态的，随着时间和环境而变化。互动有一个内在的节奏，经常发生在一系列的时间尺度。交互的时间流通常被聚合到动态网络中用于时间分析。此分析的结果很大程度上受原始数据聚合的分辨率的影响。基础过程的固有时间尺度与执行分析的时间尺度之间的不匹配可能掩盖重要的见解并导致错误的结论。在本章中，我们描述了识别交互流的固有时间尺度范围以及找到与这些尺度相匹配的动态网络表示的挑战。我们描述了可能的形式化的问题，确定相互作用的内在时间尺度，并提出了一些初步的方法来解决它，注意到这些方法的优点和局限性。这是一个新兴的研究领域，我们的目标是突出其重要性，并为进一步的调查建立计算基础。
Interactions, either of molecules or people, are inherently dynamic, changing with time and context. Interactions have an inherent rhythm, often happening over a range of time scales. Temporal streams of interactions are commonly aggregated into dynamic networks for temporal analysis. Results of this analysis are greatly affected by the resolution at which the original data are aggregated. The mismatch between the inherent temporal scale of the underlying process and that at which the analysis is performed can obscure important insights and lead to wrong conclusions. In this chapter we describe the challenge of identifying the range of inherent temporal scales of a stream of interactions and of finding the dynamic network representation that matches those scales. We describe possible formalizations of the problem of identifying the inherent time scales of interactions and present some initial approaches at solving it, noting the advantages and limitations of these approaches. This is a nascent area of research and our goal is to highlight its importance and to establish a computational foundation for further investigations.