随机线图中的聚类
Clustering in random line graphs
摘要：
研究了Erdös-Rényi网络、指数增长网络和无标度增长网络上的线图的度分布$P(k)$和聚类系数$C$.我们发现，这些图的度分布的字符仍然泊松，指数和幂律，分别，即在原来的网络相同。当平均度$<k>$增大时，得到的聚类系数$C$对于变换后的Erdös-Rényi网络趋于0.50，对于变换后的指数网络趋于0.53，对于变换后的无标度网络趋于0.61.这些结果接近理论值，得到的模型假设，在初始网络的度度相关性是可以忽略的。
英文摘要：
We investigate the degree distribution $P(k)$ and the clustering coefficient $C$ of the line graphs constructed on the Erdös-Rényi networks, the exponential and the scale-free growing networks. We show that the character of the degree distribution in these graphs remains Poissonian, exponential and power law, respectively, i.e. the same as in the original networks. When the mean degree $<k>$ increases, the obtained clustering coefficient $C$ tends to 0.50 for the transformed Erdös-Rényi networks, to 0.53 for the transformed exponential networks and to 0.61 for the transformed scale-free networks. These results are close to theoretical values, obtained with the model assumption that the degree-degree correlations in the initial networks are negligible.
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。
