基于密度估计的社会网络特征簇挖掘方法

摘要

A hierarchical structure extraction approach based on agglomerative clustering was proposed, and a density estimation based on topological structure was designed. By conducting the hierarchical aggregation on layers of hierarchical structure, the characteristic of clusters could be measured. The empirical study conducted on a large real data set indicates that the model and measures are interesting and meaningful, and the algorithms are effective and efficient in practice.%通过凝聚式聚类方法抽取网络的层次结构,并基于拓扑结构分析,给出了社会网络的标注密度估计函数.通过对密度估计函数在网络层次结构上的聚合操作,计算聚簇的特征性指标,从而达到发现特征聚簇的目的.在大规模的真实数据上对这些方法和模型进行了验证,实验结果表明,所提出的思路和模型是合理的,算法是高效、可伸缩的.