Pozo Roldan
National Institute of Standards and Technology, Gaithersburg, MD 20899.
J Res Natl Inst Stand Technol. 2016 Feb 8;121:1-16. doi: 10.6028/jres.121.001. eCollection 2016.
Given an undirected network, we describe a two-dimensional graphical measure based on the connected component distribution of its degree-limited subgraphs. This process yields an unambiguous visual , which reveals important network properties. It can be used as a classification tool, as graphs from related application areas have striking similarities. It can also be used as an efficient algorithm to demonstrate graph non-isomorphism for large graphs with identical degree distributions. Finally, it can be used as an analysis tool to help distinguish real-world networks from their synthetic counterparts.
对于一个无向网络，我们基于其度受限子图的连通分量分布描述了一种二维图形度量。这个过程产生了一个明确的可视化结果，它揭示了重要的网络属性。它可以用作分类工具，因为来自相关应用领域的图有显著的相似性。它还可以用作一种高效算法，用于证明具有相同度分布的大型图的非同构性。最后，它可以用作分析工具，以帮助区分真实世界的网络与其合成对应物。
