Finding Community Structure in Networks by Gravitation Algorithm
We propose a new algorithm for discovering community structure (natural divisions of networks nodes into densely connected sub-networks) in networks. Our algorithm has two definitive features: first, the edges and vertices of network are assigned a weight to represent the mass of each vertex and distance of each edge at the same time, and second, the algorithm involves a iterative mergence of two vertices and communities with the largest gravitation (imitating the concept and equation from Newtons law of universal gravitation) to split the network into communities. The algorithm is very flexible, both the assignment of weight and calculation of gravitation can be specifically design for specific problems. We demonstrate that our algorithm is highly effective at discovering community structure in real-world networks with primary pathways (e.g. urban bus traffic networks and cellular metabolic networks), and show it can be used to study the evolution of complex networked systems.
Bus traffic network urbanization cluster power-law
Yong Min Xiaogang Jin Bo Gao Jie Chang Ying Ge
College of Computer Science Zhejiang University Hangzhou, Zhejiang 310027, China Deputy Director of General Office Zhejiang Institute of Communications Hangzhou, Zhejiang 311112, hi College of Life Science Zhejiang University Hangzhou, Zhejiang 310058, China
国际会议
桂林
英文
191-194
2010-11-17（万方平台首次上网日期，不代表论文的发表时间）