Network-based modeling of complex systems and data using the language of graphs has become an essential topic across a range of different disciplines. Arguably, this graph-based perspective derives its success from the relative simplicity of graphs: A graph consists of nothing more than a set of vertices and a set of edges, describing relationships between pairs of such vertices. This simple combinatorial structure makes graphs interpretable and flexible modeling tools. The simplicity of graphs as system models, however, has been scrutinized in the literature recently. Specifically, it has been argued from a variety of different angles that there is a need for higher-order networks, which go beyond the paradigm of modeling pairwise relationships, as encapsulated by graphs. In this survey article we take stock of these recent developments. Our goals are to clarify (i) what higher-order networks are, (ii) why these are interesting objects of study, and (iii) how they can be used in applications.
翻译:使用图形语言的复杂系统和数据的网络型建模已成为一系列不同学科中的一个基本主题。 可以说,基于图形的视角之所以成功,是因为图表相对简单: 图表由一组脊椎和一组边缘组成,描述这些脊椎的两对之间的关系。 这个简单的组合结构使图表可以解释和灵活建模工具。 图表的简单性作为系统模型,最近已在文献中进行了仔细研究。 具体地说,人们从不同的角度认为,需要更高级网络,这超出了图表所概括的成对关系模型范式。 在本调查文章中,我们总结了这些最近的动态。 我们的目标是澄清(一) 更高级网络是什么, (二) 这些网络为什么是有趣的研究对象, (三) 如何在应用中使用这些网络。