An algorithm for detecting community structure of complex networks based on clustering

作者：Bin Sheng; Sun Gengxin^*

来源：International Journal of Digital Content Technology and Its Applications, 2011, 5(7): 326-334.

DOI：10.4156/jdcta.vol5.issue7.41

• Clustering
• Community structures
• Complex networks
• Fuzzy C mean
• k-Means algorithm
• Network node
• Overlapping communities
• Similarity measure

There are considerable interest in algorithms for detecting community structure, which is fundamental for analyzing the relationship between structure and function in complex networks. In this paper, after the introduction of some traditional approaches for detecting community structure and data mining clustering algorithms, we propose Mapping Vertex into Vector(MVV) algorithm, which can convert network nodes to vector, based on the algorithm, we propose K-means algorithm for detecting community structure based on MVV, and use fuzzy c-means to deal with overlapping community. Finally, experiments show that the algorithm presented in this paper is of high accuracy with good performance.

• 出版日期2011