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| Overlapping Community Discovery Based on Node Hierarchy and Label Propagation Gain |
| CHEN Yu-Zhong, SHI Song, CHEN Guo-Long, YU Zhi-Yong |
1.College of Mathematics and Computer Science, Fuzhou University, Fuzhou 350108
2.Fujian Key Laboratory of Network Computing and Intelligent Information Processing, Fuzhou University, Fuzhou 350108 |
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Abstract The time complexity of multi-label propagation algorithm (MLPA) is nearly linear. However, when it is applied to overlapping community discovery, the accuracy and the stability of MLPA are poor. Inspired by the idea that overlapping nodes are more probable to appear in the boundary regions of different communities, an overlapping community discovery algorithm based on node hierarchy and label propagation gain is proposed in this paper. Firstly, the improved single label propagation with node centrality and community distribution constraints is utilized to unfold preliminary non-overlapping communities and centrality values of nodes are calculated by local information in the propagation process simultaneously. Furthermore, node hierarchy partition function is defined according to centrality values of nodes and employed to mark the hierarchy of each node in its respective community. Finally, based on the label propagation gain among nodes, a new multi-label updating rule is designed to obtain the final overlapping communities. Extensive experimental results on synthetic and real-world networks validate that the proposed algorithm effectively improves the accuracy and stability.
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Received: 05 May 2014
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2015, Vol. 28 
