Detecting Overlapping Community Structure via an Improved Spread Algorithm Based on PCA
Community structure is an important property to uncover structural and functional features in various complex systems.In this paper,we propose an improved spread algorithm based on Principal Component Analysis (PCA) to detect overlapping community structure in the complex network.The proposed algorithm uses PCA to choose the optimal number of eigenvectors self-adaptively,then calculates the Laplace matrix and maps nodes into low dimension subspace.At last,the FCM algorithm is used to reveal the overlapping community structure.The simulation results in real world and artificial networks show that the proposed algorithm can detect reasonable overlapping communities in the complex network.
Community detection Spectral Analysis PCA
Lin LI Zheng-Min XIA Sheng-Hong LI Zhi-Hua HUANG Song-Nian LU
School of Electronic Information and Electrical Engineering,Shanghai Jiaotong University,Shanghai,200240,China
国内会议
杭州
英文
1-7
2014-10-18(万方平台首次上网日期,不代表论文的发表时间)