论文标题
网络中的密集和稀疏顶点连接
Dense and sparse vertex connectivity in networks
论文作者
论文摘要
开发了用于分析复杂网络结构的不同方法产生了大量研究。至少在社交网络领域，研究主要涉及对社区的检测和分析。在本文中，我们挑战了这些方法，并专注于具有有意义的本地互动能够识别社区内部组织或社区组装方式的节点。我们提出了一种算法Itrich，以基于图形分解为连续的，较少且密度较少的层。我们的方法对合成和真实数据集进行了测试，并与其他方法（例如社区检测或K核分解）很好地分配。
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.
