Abstract
Community structure is one of the most important features in complex networks. However, with increasing of network scale, some existing methods cannot effectively detect the community structure of complex network, and the available methods mostly aimed at non-overlapping networks. In this paper, we focus on overlapping community detection in large-scale networks, because most of the communities in real-world networks are overlapped. In order to improve the accuracy of large-scale overlapping community detection, we suggest a community detection method based on node priority. The proposed algorithm has two advantages: (1) We define a priority function \({\text{f}}_{\text{NN}}\) to assess the closeness between adjacent nodes. It explores the potential community structure in advance and reduces the scale of networks. (2) We employ NSGA-II and select all Pareto fronts to mine large-scale overlapping communities. The proposed algorithm is tested by the artificial and real datasets. The results show that the proposed algorithm can effectively improve the accuracy of community detection and has better optimization effect.
Similar content being viewed by others
References
Pizzuti C, Rombo SE (2014) Algorithms and tools for protein-protein interaction networks clustering, with a special focus on population-based stochastic methods. Bioinformatics 30(10):1343–1352
Adamic LA et al (2000) Power-law distribution of the World Wide Web. Science 287(5461):2115
Gong M, Ma L, Zhang Q, Jiao L (2012) Community detection in networks by using multi-objective evolutionary algorithm with decomposition. Phys A 391(15):4050–4060
Lancichinetti A, Radicchi F, Ramasco JJ, Fortunato S (2011) Finding statistically significant communities in networks. PLoS ONE 6(4):e18961
Wen X et al (2017) A maximal clique based multiobjective evolutionary algorithm for overlapping community detection. IEEE Trans Evol Comput 21(3):363–377
Zhang L, Pan H, Su Y, Zhang X, Niu Y (2017) A mixed representation-based multiobjective evolutionary algorithm for overlapping community detection. IEEE Trans Cybern 47(9):2703–2716
Shi C, Yan Z, Wang Y, Cai Y, Wu B (2010) A genetic algorithm for detecting communities in large-scale complex networks. Adv Complex Syst 13(1):3–17
Amiri B, Hossain L, Crawfordd JW (2011) An efficient multiobjective evolutionary algorithm for community detection in social networks. In: Proceedings of the IEEE congress evolutionary computation, pp 2193–2199
Pizzuti C (2008) GA-Net: a genetic algorithm for community detection in social networks. In: Proceedings of the international conference on parallel problem solving nature, pp 1081–1090
Shi C, Yan Z, Cai Y, Wu B (2012) Multi-objective community detection in complex networks. Appl Soft Comput 12(2):850–859
Li Y, Wang Y, Chen J, Jiao L, Shang R (2015) Overlapping community detection through an improved multi-objective quantum-behaved particle swarm optimization. J Heuristics 21(4):1–27
Ma X et al (2016) A multi-objective evolutionary algorithm based on decision variable analyses for multi-objective optimization problems with large scale variables. IEEE Trans Evol Comput 20(2):275–298
Folino F, Pizzuti C (2014) An evolutionary multiobjective approach for community discovery in dynamic networks. IEEE Trans Knowl Data Eng 26(8):1838–1852
Liu X, Murata T (2010) Advanced modularity-specialized label propagation algorithm for detecting communities in networks. Phys A 389(7):1493–1500
Chen Q, Wu TT, Fang M (2013) Detecting local community structures in complex networks based on local degree central nodes. Phys A 392:529–537
Palla G, Derényi I, Farkas I, Vicsek T (2005) Uncovering the overlapping community structure of complex networks in nature and society. Nature 7043(435):814–818
Gregory S (2010) Finding overlapping communities in networks by label propagation. New J Phys 12(10):103018
Shang RH, Bai J, Jiao L, Jin C (2013) Community detection based on modularity and an improved genetic algorithm. Phys A 392:1215–1231
Newman MEJ, Girvan M (2004) Phys Rev E 69:026113
Lai D, Lu H, Nardini C (2010) Enhanced modularity-based community detection by random walk network preprocessing. Phys Rev E 81(6):066118
Rotta R, Noack A (2011) Multilevel local search algorithms for modularity clustering. J Exp Algorithmics 16(2):2–3
Fortunato S, Barthelemy M (2007) Resolution limit in community detection. Proc Natl Acad Sci 114(1):36–41
Gong MG, Fu B, Jiao LC, Du HF (2011) Memetic algorithm for community detection in networks. Phys Rev E 00:006100
Gong M, Cai Q, Chen X, Ma L (2014) Complex network clustering by multiobjective discrete particle swarm optimization based on decomposition. IEEE Trans Evol Comput 18:82–97
Liu J, Zhong W, Abbass HA, Green DG (2010) Separated and overlapping community detection in complex networks using multiobjective evolutionary algorithms. In: IEEE congress on evolutionary computation, Barcelona, Spain, 18–23 July 2010, pp 1–7. https://doi.org/10.1109/CEC.2010.5586522
Zhao Y, Li S, Feng J (2017) Overlapping community detection in complex networks using multi-objective evolutionary algorithm. Comput Appl Math 36(1):749–768
Gong M, Cai Q, Chen X, Ma L (2014) Complex network clustering by multiobjective discrete particle swarm optimization based on decomposition. IEEE Trans Evol Comput 18(1):82–97
Danon L, Diaz-Guilera A, Duch J, Arenas A (2005) Comparing community structure identification. J Stat Mech: Theory Exp 09:09008
Shen H, Cheng X, Cai K, Hu MB (2009) Detect overlapping and hierarchical community structure. Phys A 388:1706
Gregory S (2008) A fast algorithm to find overlapping communities in networks. In: Machine learning and knowledge discovery in databases. pp 408–423
Palla G, Derényi I, Farkas I, Vicsek T (2005) Uncovering the overlapping community structure of complex networks in nature and society. Nature 435:814–818
Zachary W (1977) An information flow model for conflict and fission in small groups. J Anthropol Res 33:452–473
Lusseau D, Schneider K, Boisseau OJ, Haase P, Slooten E, Dawson SM (2003) The bottlenose dolphin community of doubtful sound features a large proportion of long-lasting associations. Behav Ecol Sociobiol 54:396–405
Girvan M, Newman MEJ (2002) Community structure in social and biological networks. Proc Natl Acad Sci USA 99:7821–7826
Newman MEJ (2006) Finding community structure in networks using the eigenvectors of matrices. Phys Rev E 74(3):036104
Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small-world’ networks. Nature 393(6684):440–442
Newman MEJ, (2013) Network data. Available at. http://www-personal.umich.edu
Leskovec J, Kleinberg J, Faloutsos C (2005) Graphs over time: densification laws, shrinking diameters and possible explanations. In: Proceedings of the eleventh ACM SIGKDD international conference on knowledge discovery in data mining, pp 177–187
Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grant Nos. U1504613).
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Chai, Z., Liang, S. A node-priority based large-scale overlapping community detection using evolutionary multi-objective optimization. Evol. Intel. 13, 59–68 (2020). https://doi.org/10.1007/s12065-019-00250-5
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12065-019-00250-5