Ant colony clustering with fitness perception and pheromone diffusion for community detection in complex networks

Junzhong Ji, Xiangjing Song, Chunnian Liu and Xiuzhen Zhang

Physica A: Statistical Mechanics and its Applications, 2013, vol. 392, issue 15, 3260-3272

Abstract: Community structure detection in complex networks has been intensively investigated in recent years. In this paper, we propose an adaptive approach based on ant colony clustering to discover communities in a complex network. The focus of the method is the clustering process of an ant colony in a virtual grid, where each ant represents a node in the complex network. During the ant colony search, the method uses a new fitness function to percept local environment and employs a pheromone diffusion model as a global information feedback mechanism to realize information exchange among ants. A significant advantage of our method is that the locations in the grid environment and the connections of the complex network structure are simultaneously taken into account in ants moving. Experimental results on computer-generated and real-world networks show the capability of our method to successfully detect community structures.

Keywords: Complex network; Community structure detection; Ant colony clustering; Fitness perception; Pheromone diffusion model (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:392:y:2013:i:15:p:3260-3272

DOI: 10.1016/j.physa.2013.04.001

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