Abstract
Recently, community detection in complex networks has attracted more and more attentions. However, real networks usually have number of overlapping communities. Many overlapping community detection algorithms have been developed. These methods usually consider the overlapping community detection as a single-objective optimization problem. This paper regards it as a multi-objective optimization problem and proposes a Multi-Objective evolutionary algorithm for Overlapping Community Detection (MOOCD). This algorithm simultaneously optimize two objective functions to get proper community partitions. Experiments on artificial and real networks illustrate the effectiveness of MOOCD.
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Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., Hwang, D.U.: Complex networks: Structure and dynamics. Physics Report 424(4-5), 175–308 (2006)
Guimera, R., Amaral, L.A.N.: Functional cartography of complex metabolic networks. Nature 433, 895–900 (2005)
Newman, M.E.J., Girvan, M.: Finding and evaluating community structure in networks. Physics Review E 69(026113) (2004)
Radicchi, F., Castellano, C., Cecconi, F., Loreto, V., Parisi, D.: Defining and identifying communities in networks. Proceedings of the National Academy of Sciences 101(9), 2658–2663 (2004)
Pothen, A., Sinmon, H., Liou, K.P.: Partitioning sparse matrices with eigenvectors of graphs. SIAM Journal on Matrix Analysis and Applications (11), 430–452 (1990)
Kannan, R., Vempala, S., Vetta, A.: On clusterings: good, bad and spectral. Journal of the ACM 51(3), 497–515 (2004)
Pizzuti, C.: GA-net: A genetic algorithm for community detection in social networks. In: Rudolph, G., Jansen, T., Lucas, S., Poloni, C., Beume, N. (eds.) PPSN 2008. LNCS, vol. 5199, pp. 1081–1090. Springer, Heidelberg (2008)
Shi, C., Yan, Z.Y., Wang, Y., Cai, Y.N., Wu, B.: A genetic algorithm for detecting communities in large-scale complex networks. Advance in Complex System 13(1), 3–17 (2010)
Tasgin, M., Bingol, H.: Community detection in complex networks using genetic algorithm. arXiv:cond-mat/0604419 (2006)
Duch, J., Arenas, A.: Community detection in complex networks using extremal optimization. Physical Review E 72(2), 027104 (2005)
Palla, G., Derenyi, I., Farkas, I., Vicsek, T.: Uncovering the overlapping community structure of complex networks in nature and society. Nature 435, 814–818 (2005)
Gregory, S.: An Algorithm to Find Overlapping Community Structure in Networks. In: Kok, J.N., Koronacki, J., Lopez de Mantaras, R., Matwin, S., Mladenič, D., Skowron, A. (eds.) PKDD 2007. LNCS (LNAI), vol. 4702, pp. 91–102. Springer, Heidelberg (2007)
Pizzuti, C.: Overlapping Community Detection in Complex Networks. ACM (2009)
Cai, Y., Shi, C., Dong, Y., Ke, Q., Wu, B.: A Novel Genetic Algorithm for Overlapping Community Detection. In: Tang, J., King, I., Chen, L., Wang, J. (eds.) ADMA 2011, Part I. LNCS (LNAI), vol. 7120, pp. 97–108. Springer, Heidelberg (2011)
Shen, H., Cheng, X., Cai, K., Hu, M.B.: Detect overlapping and hierarchical community structure in networks. Physica A 388, 1706–1712 (2009)
Xiaohua, W., Licheng, J., Jianshe, W.: Adjusting from disjoint to overlapping community detection of complex networks. Physica A 388, 5045–5056 (2009)
Maoguo, G., Lijia, M., Qingfu, Z., Licheng, J.: Community detection in networks by using multiobjective evolutionary algorithm with decomposition. Physica A 391, 4050–4060 (2012)
Maoguo, G.: Complex Network Clustering by Multiobjective Discrete Particle Swarm Optimization Based on Decomposition. IEEE Transactions on Evolutionary Computation (2013), doi:10.1109/TEVC.2013.2260862
Shi, C., Yan, Z., Cai, Y., Wu, B.: Multi-objective community detection in complex networks. Applied Soft Computing 12(2), 850–859 (2012)
Ahn, Y.Y., Bagrow, J.P., Lehmann, S.: Link communities reveal multiscale com-plexity in networks. Nature 466, 761–764 (2010)
Palla, G., Dernyi, I., Farkas, I., Vicsek, T.: Uncovering the overlapping community strcture of complex networks in nature and society. Nature 435, 814 (2005)
Corne, D.W., Jerram, N.R., Knwoles, J.D., Oates, M.J.: PESA-II: Region-based Selection in Evolutionary Multiobjective Optimization. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2001) (2001)
Radicchi, F., Castellano, C., Cecconi, F., Loreto, V., Parisi, D.: Defining and identifying communities in networks. PNAS 101(9), 2658–2663 (2004)
Clauset, A., Newman, M.E.J., Moore, C.: Finding community structure in very large networks. Physical Review E 70(6), 06611 (2004)
Fortunato, S., Barthelemy, M.: Resolution limit in community detection. Proceedings of the National Academy of Sciences 104(1), 36–41 (2007)
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Du, J., Lai, J., Shi, C. (2013). Multi-Objective Optimization for Overlapping Community Detection. In: Motoda, H., Wu, Z., Cao, L., Zaiane, O., Yao, M., Wang, W. (eds) Advanced Data Mining and Applications. ADMA 2013. Lecture Notes in Computer Science(), vol 8347. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53917-6_44
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DOI: https://doi.org/10.1007/978-3-642-53917-6_44
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