Refinement of the community detection performance by weighted relationship coupling

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• 作者：DONG MIN ; KAI YU ; HUI-JIA LI
• 关键词：Network analysis ; community structure ; weighting scheme ; k ; strength relationship ; modularity
• 刊名：Pramana
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：88
• 期：3
• 全文大小：
• 刊物类别：Physics and Astronomy
• 刊物主题：Physics, general; Astronomy, Observations and Techniques; Astrophysics and Astroparticles;
• 出版者：Springer India
• ISSN：0973-7111
• 卷排序：88

文摘

The complexity of many community detection algorithms is usually an exponential function with the scale which hard to uncover community structure with high speed. Inspired by the ideas of the famous modularity optimization, in this paper, we proposed a proper weighting scheme utilizing a novel k-strength relationship which naturally represents the coupling distance between two nodes. Community structure detection using a generalized weighted modularity measure is refined based on the weighted k-strength matrix. We apply our algorithm on both the famous benchmark network and the real networks. Theoretical analysis and experiments show that the weighted algorithm can uncover communities fast and accurately and can be easily extended to large-scale real networks.