A label propagation approach based on local optimization

Xiaohong Zhang (), Yulin Jiang (), Jianji Ren () and Chaosheng Tang
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Xiaohong Zhang: College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, P. R. China
Yulin Jiang: College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, P. R. China
Jianji Ren: College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, P. R. China
Chaosheng Tang: College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo 454000, P. R. China

International Journal of Modern Physics C (IJMPC), 2018, vol. 29, issue 06, 1-16

Abstract: Community detection offers an important way to understand the structures and functions of social network. The label propagation algorithm has attracted vast attention since it is very suitable for discovering communities from large-scale networks. However, the algorithm suffers from the instability and inefficiency problem caused by the random policies it adopted. In this paper, we propose a novel label propagation approach based on local optimization to deal with the problem. The approach introduces a pre-propagation mechanism to optimize randomly initialized labels according to special factors, for example, node compactness. After that, it traverses and relabels nodes in the descending order of aggregate influence. The experiment results demonstrate the usefulness and effectiveness of our approach.

Keywords: Community detection; label propagation algorithm; social network; pre-propagation (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (1)

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DOI: 10.1142/S012918311850047X

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