复杂网络全局拓扑相似度计算方法实证研究

摘要

The research on similarity of complex network has important effect on many hot fields, such as chain forecasting, evolution mechanism and community detection. This article defines a new method to compute the similar-ity of different complex network based on the global topological properties. The simulation results show that the method can distinguish different complex network according to their similarity. This text also shows that there are three stages in the development process of technology trading by using the method which this text defined in the empirical research, and the similarity of the complex networks in the same stage is obviously higher than the ones those in differ-ent stages which proves that the method this text defined is feasible and effective.%相似度研究对于复杂网络的链路预测、演化机制以及社团检测等相关热门研究领域都具有重要的作用，本文从网络相似度及演化的角度出发，基于提取复杂网络全局拓扑特性，定义了一种新的复杂网络相似度计算方法，仿真结果表明，该相似度计算方法可以准确表征不同复杂网络的相似程度，通过将该方法应用于技术交易中进行实证分析，发现可以将技术交易分为三个不同的阶段，每一阶段内的复杂网络之间相似度明显高于该阶段外的复杂网络，证实了本文提出的相似度计算方法具有可行性与有效性。