Abstract
Community detection is a fundamental task in discovering complex network. Maximal cliques are found to play significant roles in communities. This paper proposes an efficient algorithm OMC for detecting communities based on maximal cliques. Subordinate maximal cliques are removed and remaining cliques are regarded as initial communities. Then small communities are merged into larger ones according to a fitness function. The proposed algorithm is able to uncover both overlapping and hierarchical communities in high speed. Experimental results on various real-word networks have proven that the method performed well in detecting communities.
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© 2015 Springer Science+Business Media Singapore
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Huang, Z., Wang, Z., Zhang, Z. (2015). Detecting Overlapping and Hierarchical Communities in Complex Network Based on Maximal Cliques. In: Zhang, X., Sun, M., Wang, Z., Huang, X. (eds) Social Media Processing. SMP 2015. Communications in Computer and Information Science, vol 568. Springer, Singapore. https://doi.org/10.1007/978-981-10-0080-5_17
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DOI: https://doi.org/10.1007/978-981-10-0080-5_17
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