针对传统基于标签传播的重叠社区识别方法存在较强的随机性,以及需要预设相关阈值来辅助完成社区识别等缺陷,提出基于多核心标签传播的重叠社区识别方法(OMKLP).在分析节点度以及节点与邻居节点的局部覆盖密度后提出核心节点评价模型,并在此基础上给出局部核心节点识别方法;基于局部核心节点,提出新的面向重叠社区的异步标签传播策略,该策略能够快速地识别出社区内部节点与边界节点,以获得重叠社区结构;提出重叠节点分析方法,进一步提高识别重叠节点准确度.OMKLP算法无需掌握任何先验知识,仅在掌握网络基本信息(点、边)基础上,便能够准确识别出重叠社区结构,从而有效解决了传统标签传播算法所存在的缺陷.在基准网络和真实网络上进行测试,并与多个经典算法进行对比分析,实验结果验证了所提算法的有效性和可行性.%In view of the strong randomness and pre-setting the related threshold of traditional overlapping community detection method based on label propagation, overlapping community detection in complex networks based on multi kernel label propagation (OMKLP) was proposed. Evaluation model of kernel nodes was proposed after analyzing the node's degree and local covering density of nodes and their neighbor nodes. And on this basis, the detection method of local kernel nodes was also presented. Based on local kernel nodes, a new asynchronous label propagation strategy ori-ented to overlapping community was proposed, which can rapidly distinguish inner nodes and outer nodes of communi-ties so as to obtain overlapping community structure. The analysis method of overlapping nodes was proposed to increase the accuracy of detecting overlapping nodes. Without any prior knowledge, only on the basis of the basic network infor-mation (nodes and links), the algorithm can detect the structure of overlapping communities accurately. Therefore, it ef-fectively solved the defect of the traditional label propagation algorithm. The algorithm was tested over benchmark net-works and real-world networks and also compared with some classic algorithms. The experiment results verify the valid-ity and feasibility of OMKLP.
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