选取失眠症作为研究对象，采用复杂网络节点中心性评估和聚类分析方法，探索失眠症辨证论治中核心中药及配伍规律。首先，通过构建失眠中药网络模型，引入复杂网络节点中心性评估单指标算法，挖掘中药网络的核心节点；其次，利用基于节点中心性的聚类算法CNM-Centrality对中药网络进行聚类划分，准确地找到药物间的配伍规律。

Using node centrality evaluation algorithms and clustering algorithms in complex networks, this paper selects insomnia as study object, and explores the core Chinese materia medica (CMM) and CMM compatibility regularity of syndrome differentiation and treatment. Firstly, we construct the CMM network model of insomnia, and discover the core CMM nodes in this network using single-index evaluation algorithms. Then, the CMM network can be divided by the clustering algorithm CNM-centrality based on node centrality, and the compatibility regularity among CMM can be found accurately.

2017年度湖北省教育厅科研计划项目-基于优化聚类算法的中医失眠证候判别分析研究（Q20172005）