Research On Community Discovery And Layout Algorithm For Complex Network

Human society has long been networked.Complex networks such as the World Wide Web,social networks,and transportation networks are ubiquitous in people's lives.Complex network topology is an effective means to understand and explain the dynamic behavior or process of the network.For computer networks,the spread of computer viruses,information or spread of rumors in social networks,and other highly applicable network behavior,need to rely on network topology for analysis and research.Discovering community structures in complex networks through community discovery algorithms and using visual layout methods to display the community structure of complex networks can help researchers explore useful information in the network.The existing community discovery algorithms have the problems of low community quality and low efficiency of algorithm execution,and the FR algorithm community structure is not obvious,and the algorithm is not suitable for complex networks.This paper presents an improved community discovery algorithm based on Louvain algorithm and an improved community layout algorithm based on FR algorithm.First,based on the Louvain algorithm,a community discovery algorithm for complex networks is studied.The characteristics of complex networks include small-world and scale-free,and the degree of nodes is represented by the law of power distribution,and the degree of most nodes is low while the degree of some nodes is high.In a complex network,nodes with high degrees of degree and nodes with low degree of neighboring degrees easily constitute a community.In order to solve the problem of low efficiency and unreasonable community division of Louvain algorithm,by selecting important nodes among important nodes to control the trend of over-convergence of large communities,reducing the iterative cycle of the algorithm,and quickly merging small communities in the iterative process.,improve the efficiency of the algorithm,while improving the quality of community division.The experimental results show that the optimization of the improved Louvain algorithm has improved the quality of community classification and algorithm efficiency.Secondly,based on the FR algorithm,a community layout algorithm is studied.The algorithm can display the network community structure and optimize the gravitation and repulsion model of the community.The gravitational calculation takes into account theintimacy information of the nodes,and the repulsive force calculation considers the nodes.The degree of importance information makes the gravitational and repulsive calculations more efficient.Combine community discovery algorithm execution results and layout community structure.The experimental results show that the improved algorithm effectively improves the efficiency of algorithm execution and makes the community structure layout more clear.