计算机技术与发展2024，Vol.34Issue(9)：174-181,8.DOI:10.20165/j.cnki.ISSN1673-629X.2024.0157
基于SLPA改进的重叠社团检测算法
Improved Overlapping Community Detection Algorithm Based on SLPA
摘要
Abstract
SLPA(Speaker-Listener Label Propagation Algorithm)has linear time complexity and excellent detection effect on overlapping community detection tasks,but as a random algorithm,its repeated random selection strategy limits the accuracy of the algorithm and the results of the algorithm are unstable.In addition,when the selected threshold is low,a large number of small communities and overlapping nodes are easy to appear.Aiming at the above problems,an improved algorithm with higher accuracy and better stability is proposed.In the initialization stage of the algorithm,the ascending order of node importance calculated by node local structure entropy(LE)is used as the node update sequence.In the stage of label propagation,the resource allocation(RA)is used as the basis for further selection of nodes to guide the direction of label propagation.In the post-processing stage,pairwise comparison to the selected community set is added to remove the nested communities.The proposed algorithm is verified on real networks and artificial networks,and compared with five classical algorithms by using overlapping normalized mutual information(NMIov)and Extended Modularity(EQ).Experiments show that the improved algorithm has advantages in accuracy compared with the classical algorithm,and has good robustness in both real networks and artificial networks.Compared with the original algorithm,the results of the improved algorithm are more concentrated and the stability of the algorithm is improved.关键词
复杂网络/重叠社团检测/标签传播算法/局部结构熵/SLPAKey words
complex network/overlapping community detection/label propagation algorithm/local structure entropy/SLPA分类
信息技术与安全科学引用本文复制引用
胡志涛,余路粉,潘文林..基于SLPA改进的重叠社团检测算法[J].计算机技术与发展,2024,34(9):174-181,8.基金项目
国家自然科学基金(62362071) （62362071）
