基于节点综合相似度的多标签传播社区划分算法

o solve the problem that recent research about multi label propagation community division algorithm adopted the random sequence strategy to result in unstable result of community division and poor community quality, this paper proposed a Multi-label Propagation Algorithm Based on the Node Comprehensive Similarity (MLPA-NCS) for community division. This paper chose the descending order of node potential impact as the node selection order in order to solve the problem of the instability of the propagation. Node synthesis similarity could be calculated based on the theme of node similarity and link correlation, and its descending order was used as the order of neighboring nodes traversal when updating the node label to improve the quality of the communities found. This paper used real data sets and artificial network data to compare the results of several algorithms. The results show that the algorithm is effective and feasible and able to make the result of community division more stable while the quality of community more effectively.