Abstract
There is a surge of community detection on complex network analysis in recent years, since communities often play special roles in the network systems. However, many community structures are overlapping in real word. For example, a professor collaborates with researchers in different fields. In this paper, we propose a novel algorithm to discover overlapping communities. Different from conventional algorithms based on node clustering, our algorithm is based on edge clustering. Since edges usually represent unique relations among nodes, edge clustering will discover groups of edges that have the same characteristics. Thus nodes naturally belong to multiple communities. The proposed algorithm apply a novel genetic algorithm to cluster on edges. A scalable encoding schema is designed and the number of communities can be automatically determined. Experiments on both artificial networks and real networks validate the effectiveness and efficiency of the algorithm.
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References
Pereira, J.B., Enright, A.J., Ouzounis, C.A.: Detection of functional modules from protein interaction networks. Proteins: Structure, Fuctions, and Bioinformatics 54, 49–57 (2004)
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)
Baumes, J., Goldberg, M., Magdon-Ismail, M.: Efficient Identification of Overlapping Communities. In: Kantor, P., Muresan, G., Roberts, F., Zeng, D.D., Wang, F.-Y., Chen, H., Merkle, R.C. (eds.) ISI 2005. LNCS, vol. 3495, pp. 27–36. Springer, Heidelberg (2005)
Zhang, S.H., Wang, R.S., Zhang, X.S.: Identification of overlapping community structure in complex networks using fuzzy c-means clustering. Phisica A 374, 483–490 (2007)
Gregory, S.: An Algorithm to Find Overlapping Communities 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)
Gregory, S.: A fast algorithm to find overlapping communities in networks. In: PKDD, pp. 408–423 (2008)
Lancichinetti, A., Fortunato, S., Kertesz, J.: Detecting the overlapping and hierarchical community structure of complex networks (2008), arXiv:0802.1281,physics.soc-ph
Ahn, Y.Y., Bagrow, J.P., Lehmann, S.: Link communities reveal multiscale complexity in networks. Nature 466, 761–764 (2010)
Pizzuti, C.: Overlapping Community Detection in Complex Networks. ACM (2009)
Kumpula, J.M., et al.: Sequential algorithm for fast clique percolation. Phys. Rev. E 78, 026109 (2008)
Shi, C., Yan, Z.Y., Wang, Y., Cai, Y.N., Wu, B.: A Genetic Algorithm for Detecting Communities in Large-scale Complex Networks. ACS 13(1), 3–17 (2010)
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Cai, Y., Shi, C., Dong, Y., Ke, Q., Wu, B. (2011). A Novel Genetic Algorithm for Overlapping Community Detection. In: Tang, J., King, I., Chen, L., Wang, J. (eds) Advanced Data Mining and Applications. ADMA 2011. Lecture Notes in Computer Science(), vol 7120. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25853-4_8
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DOI: https://doi.org/10.1007/978-3-642-25853-4_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25852-7
Online ISBN: 978-3-642-25853-4
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