A Micro-Community Structure Merging Model Using a Community Sample Matrix

【摘要】 Detecting an overlapping and hierarchical community structure can give a significant insight into structural and functional properties in complex networks.We propose a micro-community structure merging model to detect overlapping and hierarchical communities.The algorithm maps communities to random variables using the community sample matrix to evaluate similarity between communities.After finding density-based microcommunity structures,the algorithm merges these reasonable micro-communities iteratively to form communities.Simulation results in three real networks show that the proposed algorithm is more accurate than some existing mechanisms.In this way,we can obtain a detailed understanding of the overlapping and hierarchical communities.更多还原

【Abstract】 Detecting an overlapping and hierarchical community structure can give a significant insight into structural and functional properties in complex networks.We propose a micro-community structure merging model to detect overlapping and hierarchical communities.The algorithm maps communities to random variables using the community sample matrix to evaluate similarity between communities.After finding density-based microcommunity structures,the algorithm merges these reasonable micro-communities iteratively to form communities.Simulation results in three real networks show that the proposed algorithm is more accurate than some existing mechanisms.In this way,we can obtain a detailed understanding of the overlapping and hierarchical communities.更多还原