There have been rapid developments in model-based clustering of graphs, also known as block modelling, over the last ten years or so. We review different approaches and extensions proposed for different aspects in this area, such as the type of the graph, the clustering approach, the inference approach, and whether the number of groups is selected or estimated. We also review models that combine block modelling with topic modelling and/or longitudinal modelling, regarding how these models deal with multiple types of data. How different approaches cope with various issues will be summarised and compared, to facilitate the demand of practitioners for a concise overview of the current status of these areas of literature.

中文翻译：

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图聚类的随机块模型和扩展综述

在过去的十年左右的时间内，基于图的基于模型的图聚类（也称为块建模）得到了飞速发展。我们回顾了针对该领域不同方面提出的不同方法和扩展，例如图的类型，聚类方法，推理方法以及是否选择或估计了组数。我们还回顾了将块建模与主题建模和/或纵向建模相结合的模型，有关这些模型如何处理多种类型的数据。将总结和比较不同方法应对各种问题的方式，以方便从业人员对这些文学领域的现状进行简要概述。