基于优化的复杂网络聚类方法综述

Overview on Optimization-based Clustering Algorithms in Complex Networks

网络簇结构是复杂网络最普遍和最重要的拓扑属性之一,具有同簇节点相互连接密集、异簇节点相互连接稀疏的特点。网络簇结构挖掘在生物学、计算机科学和社会学等多个领域都具有重要意义。近年来,针对不同类型的大规模复杂网络,提出了很多寻找网络簇结构的算法。综述了近年来最新的比较有代表性的基于优化的复杂网络聚类算法,从算法思想、关键技术等方面进行分析概括,最后展望了该领域的未来研究方向。

Network clustering structure is one of the most common and important topological properties for complex networks, and enjoys the characteristics of dense interconnection between the nodes in same cluster and sparse interconnection between the nodes in different clusters. The excavation of network clustering structure is of great importance in the fields of biology, computer science, sociology and so on. In recent years, aiming at different types of large-scale complex networks, various community discovery algorithms are proposed. Some latest representative optimization-based clustering algorithms in complex networks are reviewed, and from aspects of algorithm idea, critical technologies, etc. , these algorithms are analyzed and summarized. Finally, the future research direction in this field is forecasted.