基于希尔伯特黄变换和K-means 聚类和数据场理论的复杂网络社团结构探寻.提出和分析了基于K-means 聚类的社团探寻算法和基于数据场理论的社团探寻算法, 并通过实验仿真验证了这两种算法的有效性.-Based on the Hilbert-Huang transform and K-means clustering and data field theory complex network of community structure explore proposed and analyzed detection algorithm based on K-means clustering societies and associations based on data field theory to explore the algorithm, and by The experimental simulation results show the effectiveness of these two algorithms.