Journal article
An efficient community detection method based on rank centrality
School of Computer and Information Technology, Beijing Jiaotong University, Beijing, 100044, China
Highlights► This work improves the performance of K-means algorithm in community detection. ► The proposed method is faster than another improved algorithm K-means++. ► This algorithm can be used in directed and weighted networks. ► The proposed method can be extended to detect overlapping communities in the networks. ► Compared with other state-of-the-art algorithms, our method is more robust.
Language: | English |
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Year: | 2012 |
Pages: | 2182-2194 |
ISSN: | 18732119 and 03784371 |
Types: | Journal article |
DOI: | 10.1016/j.physa.2012.12.013 |