【摘要】 分析了真实社会网络的特性,建立了节点间多关系网络模型.在此基础上定义了节点间相互作用的影响力等概念,提出了适用于多关系网络的社团发现算法.通过理论验证了相关定义的合理性,并针对多关系网络进行了对比实验.实验结果表明:所提出的多关系网络社团发现算法与其他经典算法相比具有较高的精确度和较低的时间复杂度,具有重要的研究意义及实用价值.更多还原

【Abstract】 The characteristics of the real social network were analyzed,and a network model with multi-relationships network between nodes was established. Based on this, the concept of influence of interaction between nodes was defined,and a community discovery algorithm for multi-relationship network( CDMN) was proposed. The rationality of the presented definitions was verified theoretically,and a series of experiments compared with other algorithms were conducted. Experimental results showed that the proposed community discovery algorithm for multi-relationship networks has higher accuracy and lower time complexity than other classical algorithms,and has important research significance and practical value.更多还原