基于SA-LEN的网络社区发现的研究

SA-LEN Based Network Community Detection

构建了一种LR-S复合网络,分别提取了L-IRS网络中的最短路径长度和RRTCS网络中的活跃度两个元素,提出了一种新的节点间相似度评价函数SA-LEN及基于节点相似度的社区划分算法。通过对多种计算机生成网络和自然网络实验发现,本文的SA-LEN的网络社区发现算法具有较高准确性。

Division of network community contributes to a better understanding of community structure and predict the behavior of complex network, and has great application value in social network, information recommendation and precision marketing, and so on. This paper builds a LR-S hierarchical network, proposed a SA-LEN evaluation function of similarity degree and a SA- LEN community detecting algorithm, based on the two factors that shortest path length of L-IRS networkand activeness of R-RTCS network. This algorithm proved to be effective in nature networks and computer generated networks.