根據我們的研究，可得到對於高密度無權重網路下最大與最小的叢聚係數的上下限。我們並設計了網路拓樸來產生最大最小叢聚係數網路，此網路拓樸擁有的最大特徵是具有極端的叢聚係數。和常用的網路模型：隨機網路模型、小世界網路模型相比較，我們提出的最大與最小模型在平均網路叢聚係數上與已知的網路模型相比更高(低)，並且發現了在高密度網路結構下，網路直徑將不再是一個特殊的網路特徵，每當網路拓樸增加連線數時，每種網路模型的網路直徑均會下降且網路直徑都為同一值，這個現象說明了，在高密度網路下，網路直徑已不會受到增加新連線而會產生巨大的變化 This paper proposed two models with extreme average clustering coefficients and small path length properties for high edge density network. High density networks are common in the analysis of social networks and biological networks. This paper studies networks with extreme statistical properties, that is, max/min clustering coefficients and short average distances. In addition to those properties, the proposed models indicated that in addition to the existing small-world network model and random network model, there are other network models that may produce clustering coefficients filling the gap between those two models and the maximal achievable clustering coefficients.
