A semi-synchronous label propagation algorithm with constraints for community detection in complex networks

Chin, J.H. and Ratnavelu, K. (2017) A semi-synchronous label propagation algorithm with constraints for community detection in complex networks. Scientific Reports, 7 (1). p. 45836. ISSN 2045-2322, DOI https://doi.org/10.1038/srep45836.

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Official URL: http://dx.doi.org/10.1038/srep45836


Community structure is an important feature of a complex network, where detection of the community structure can shed some light on the properties of such a complex network. Amongst the proposed community detection methods, the label propagation algorithm (LPA) emerges as an effective detection method due to its time efficiency. Despite this advantage in computational time, the performance of LPA is affected by randomness in the algorithm. A modified LPA, called CLPA-GNR, was proposed recently and it succeeded in handling the randomness issues in the LPA. However, it did not remove the tendency for trivial detection in networks with a weak community structure. In this paper, an improved CLPA-GNR is therefore proposed. In the new algorithm, the unassigned and assigned nodes are updated synchronously while the assigned nodes are updated asynchronously. A similarity score, based on the Sørensen-Dice index, is implemented to detect the initial communities and for breaking ties during the propagation process. Constraints are utilised during the label propagation and community merging processes. The performance of the proposed algorithm is evaluated on various benchmark and real-world networks. We find that it is able to avoid trivial detection while showing substantial improvement in the quality of detection.

Item Type: Article
Uncontrolled Keywords: Semi-synchronous; Propagation algorithm; Constraints; Community detection; Complex networks
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Institute of Mathematical Sciences
Depositing User: Ms. Juhaida Abd Rahim
Date Deposited: 06 Sep 2018 05:26
Last Modified: 06 Sep 2018 05:26
URI: http://eprints.um.edu.my/id/eprint/19166

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