4.5 Article

Uncovering the fuzzy community structure accurately based on steepest descent projection

Journal

MODERN PHYSICS LETTERS B
Volume 31, Issue 27, Pages -

Publisher

WORLD SCIENTIFIC PUBL CO PTE LTD
DOI: 10.1142/S0217984917502499

Keywords

Complex networks; community detection; fuzzy partitions; steepest descent projection

Funding

  1. National Key Research and Development Program of China [2016YFB1000901]
  2. National Natural Science Foundation of China [61672433, 61471299, 91646204, 71571093, 71372188]
  3. Fundamental Research Funds for the Central Universities [3102016JKBJJGZ07]
  4. National Center for International Joint Research on E-Business Information Processing [2013B01035]
  5. Basic Research Project from Science and Innovation Council of Shenzhen [201703063000511, 201703063000517]

Ask authors/readers for more resources

Uncovering the community structure in complex network is a hot research point in recent years. How to identify the community structure accurately in complex network is still an open question under research. There are lots of methods based on topological information, which have some good performances at the expense of longer runtimes. In this paper, we propose a new fuzzy algorithm which follows the line of fuzzy c-means algorithm. A steepest descent framework with projection by optimizing the quality function is presented under the generalized framework. The results of experiments on both real-world networks and synthetic networks show that the proposed method achieves the highest efficiency and is easy for detecting fuzzy community structure in large-scale complex networks.

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