Large Scale Complex Network Summary Algorithm and Visualization Based on K-sup Density Subgraph

There are a large number of complex networks in the real world.With the advent of the era of big data,the scale of complex network data is constantly expanding.It is difficult to analyze and visualize them.In this paper,a complex network summary algorithm based on K-sup dense subgraphs was proposed for complex networks with small-world and scale-free features.Using the homogeneity and transitivity of triangles in the network,this algorithm found the dense subgraphs in complex networks by combining the modularity maximization structure.The similar nodes in subgraphs were merged into super points.Hierarchical graphs were stored and visually displayed.As a result,the algorithm can compress large-scale complex networks effectively and keep the properties of the original network.In five real data sets,the experimental results show that the proposed algorithm is superior to the existing algorithms in terms of compression ratio,power rate and average clustering coefficient.At the same time,it also has the advantages of maintaining network topology and supporting hierarchical visualization of summary graphs in large-scale data.