Computing ( IF 3.7 ) Pub Date : 2021-06-04 , DOI: 10.1007/s00607-021-00966-2 Jia Hou Chin , Kuru Ratnavelu
The detection of community structure plays an important role in understanding the properties and characteristics of complex networks. The label propagation algorithm (LPA) emerges as a popular community detection method, due to its simplicity and low computational cost. Nonetheless, the LPA is not without its limitations so that the Semi Synchronous Constrained Label Propagation Algorithm (SSCLPA) is a modified LPA that implements various constraints to ameliorate the stability of the LPA. Aside from giving accurate and deterministic detection, it can avoid trivial detection. In this paper the SSCLPA is extended into weighted and directed networks, so that nodes which fulfill certain conditions are updated separately at the end of the algorithm. Furthermore, some modifications are performed on the propagation processes in the SSCLPA. These new features and modifications improve the time efficiency of the SSCLPA with only marginal loss in the quality of the detection. Our proposed method is tested and compared to the other community detection methods in various benchmark and real-world networks. The results showed that the proposed method is a well-balanced method with features that takes into account the stability, quality and time efficiency of the detection.
中文翻译:
使用具有节点豁免的约束标签传播算法进行社区检测
社区结构的检测对于理解复杂网络的性质和特征具有重要作用。标签传播算法(LPA)由于其简单性和低计算成本而成为一种流行的社区检测方法。尽管如此,LPA 并非没有局限性,因此半同步约束标签传播算法 (SSCLPA) 是一种修改后的 LPA,它实施了各种约束以改善 LPA 的稳定性。除了提供准确和确定性的检测外,它还可以避免琐碎的检测。在本文中,SSCLPA 被扩展为加权和有向网络,以便在算法结束时分别更新满足特定条件的节点。此外,对 SSCLPA 中的传播过程进行了一些修改。这些新功能和修改提高了 SSCLPA 的时间效率,而检测质量的损失很小。我们提出的方法经过测试,并与各种基准和现实世界网络中的其他社区检测方法进行了比较。结果表明,所提出的方法是一种平衡良好的方法,其特征兼顾了检测的稳定性、质量和时间效率。