A community detection algorithm based on structural similarity

2017 2nd International Seminar on Advances in Materials Science and Engineering

Guo, Xuchao^1 ; Hao, Xia^1 ; Liu, Yaqiong^1 ; Zhang, Li^1 ; Wang, Lu^1

College of Information Science and Engineering, Shandong Agricultural University, Taian, Taian

271018, China^1

关键词: Community detection algorithms;    Dense network;    Operating efficiency;    Structural similarity;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/231/1/012069/pdf
DOI  :  10.1088/1757-899X/231/1/012069

来源: IOP

【 摘 要 】

In order to further improve the efficiency and accuracy of community detection algorithm, a new algorithm named SSTCA (the community detection algorithm based on structural similarity with threshold) is proposed. In this algorithm, the structural similarities are taken as the weights of edges, and the threshold k is considered to remove multiple edges whose weights are less than the threshold, and improve the computational efficiency. Tests were done on the Zachary's network, Dolphins' social network and Football dataset by the proposed algorithm, and compared with GN and SSNCA algorithm. The results show that the new algorithm is superior to other algorithms in accuracy for the dense networks and the operating efficiency is improved obviously.