网络中的稠密和稀疏顶点连通度
Dense and sparse vertex connectivity in networks
摘要：
复杂网络结构分析的不同方法已经产生了大量的研究。至少在社交网络领域，研究主要解决社区的检测和分析。在本文中，我们挑战这些方法，并专注于节点，有意义的本地互动能够识别社区的内部组织或社区的方式组装。我们提出了一种算法，ItRich，来识别这种类型的节点，基于分解成连续的，越来越少的密集层的图。我们的方法是测试合成和真实的数据集和网格以及与其他方法，如社区发现或k-核心分解。
英文摘要：
The different approaches developed to analyze the structure of complex networks have generated a large number of studies. In the field of social networks at least, studies mainly address the detection and analysis of communities. In this paper, we challenge these approaches and focus on nodes that have meaningful local interactions able to identify the internal organization of communities or the way communities are assembled. We propose an algorithm, ItRich, to identify this type of nodes, based on the decomposition of a graph into successive, less and less dense, layers. Our method is tested on synthetic and real data sets and meshes well with other methods such as community detection or k-core decomposition.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
