| Author Name | Affiliation | | LI Hong bo | College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China | | BAI Jin bo | School of Economics and Management, Harbin Engineering University, Harbin 150001, China
Dept. of Computer Science and Technology, Heilongjiang Institute of Technology, Harbin 150050, China | | CHU Yan | College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China | | ZHANG Le jun | College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China |
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| Abstract: |
| The studies show that numerous complex networks have clustering effect. It is an indispensable step to identify node clusters in network, namely community, in which nodes are closely related, and in many applications such as identification of ringleaders in anti criminal and anti terrorist network, efficient storage of data in Wireless Sensor Network (WSN). At present, most of community identification methods still require the specifications of the number or the scale of community by user and still can not handle overlapping nodes. In an attempt to solve these problems, a network community identification method based on utility value is proposed, which is a function of each node’s clustering coefficient and degree. This method makes use of individual centered theory for reference and can automatically determine the number of communities. In addition, this method is an overlapping community identification method in nature. It is shown through contrastive experiments that this method is more efficient than other methods based on individual centered theory when they control the same amount of information. Finally, a research direction is proposed for network community identification method based on the individual centered theory. |
| Key words: complex network individual centered theory community identification overlapping community utility value |
| DOI：10.11916/j.issn.1005-9113.2012.02.005 |
| Clc Number:TP393 |
| Fund: |
