基于时间交互偏置影响传播模型的弱连接重叠社区检测

Weak Tie Overlapping Community Detection Based on Time Interaction Bias Influence Propagation Model

为提高弱连接重叠社区的检测识别性能,提出一种基于时间交互偏置影响传播模型的弱连接重叠社区检测算法。设计针对社区检测图模型分割的目标函数,利用群落结构对处理器负载均衡进行优化,以提高模型求解的效率。基于邻域边缘密度对近似活跃边缘进行重新定义,构建一种影响传播模型以确定用户具有高频率的相互作用,从而提高弱连接用户的识别性能。在此基础上,提出时间交互偏置社区检测方法。实验结果表明,该方法对重叠社区进行检测时具有较高的识别精度和效率。

In order to improve the detection and recognition performance of weak tie overlapping communities,this paper proposes a community detection method based on time interaction bias influence propagation model.The target function for the model segmentation of community detection graph is designed and the load balance of the processor is optimized by applying community structure,so as to improve the solution efficiency of the model.Based on the neighborhood edge density,the approximate active edge is redefined and an influence propagation model is established,which can confirm that the users have high interaction frequency and have strong recognition performance for weak tie users.On this basis,a time interaction bias community detection method based on overlapping community detection is proposed.Experimental results show that the proposed method has high recognition accuracy and efficiency when conducting detection on overlapping communities.