摘要: 信息社会中,社会网络结构的形成与演变是一个动态过程,拟态计算(Mimic Computing,MC)是根据资源、任务、安全、服务和时效性等不同约束条件,动态适应用户不同的应用需求,改进计算模式的一种计算架构,是当前适应动态多变网络环境的一种有效方法。基于拟态计算,应用当前研究前沿的传染病SIR模型,提出了基于拟态计算的社会网络划分算法(Mimic Community Clustering,MCC)。应用该方法进行网络社区划分,并用真实数据来验证模型的可行性和有效性。
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