Abstract
Bipartite networks is one of the important research object in complex networks. At present, the bipartite networks community partition is mainly aimed at how to carry out accurate community structure, while the study in the community merge strategy is relative rare. In this paper, we study community partition merger principle in single nodes of bipartite networks to propose an improved bipartite networks community detection method, which is based on Page Rank algorithm, information spreading probability model and combined with the modularity. The information of single nodes is calculated by information diffusion matrix. The value of information diffusion matrix larger than the threshold are merged every time, which quickly reduces the dimensions of the information diffusion matrix to speed up the merger of the community significantly. By comparing and analyzing experimental result of this method with other typical bipartite networks community partition algorithm on South women data set, We demonstrate the effectiveness of the proposed method.
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References
Guillaume, J.-L., Latapy, M., Le-Blond, S.: Statistical analysis of a P2P query graph based on degrees and their time-evolution. In: Sen, A., Das, N., Das, S.K., Sinha, B.P. (eds.) IWDC 2004. LNCS, vol. 3326, pp. 126–137. Springer, Heidelberg (2004)
Robins, G., Alexander, M.: Small worlds among interlocking directors: network structure and distance in bipartite graphs. Comput. Math. Organ. Theor. 10, 69–94 (2004)
Battiston, S., Catanzaro, M.: Statistical properties of corporate board and director networks. Eur. Phys. J. B 38, 345–352 (2005)
Watts, D.J., Strogatz, S.H.: Collective dynamics of small world networks. Nature 393, 440–442 (1998)
Ergun, G.: Human sexual contact network as a bipartite graph. Phys. A 308, 483–488 (2002)
Zhang, P., Li, M., Mendes J.F.F., et al.: Empirical analysis and evolving model of bipartite networks. http://arxiv.org/abs/0804.3854v1
Lehmann, S., Schwartz, M., Hansen, L.K.: Biclique communities. Phys. Rev. E 69(2), 026113 (2004)
Guimera, R., Sales-Pardo, M., Amaral, L.A.: Module identification in bipartite and directed networks. Phys. Rev. E 76, 036102 (2007)
Borgattia, S.P., Everettb, M.G.: Network analysis of 2-mod data. Soc. Netw. 19, 243–269 (1997)
Barber, M.J.: Modularity and community detection in bipartite networks. Phys. Rev. E 76, 066102 (2007)
Gao, M.: Binary network community discovery algorithm study. D. Hefei Industrial university, pp. 31–37 (2012)
Raghavan, U.N., Albert, R., Kumara, S.: Near linear time algorithm to detect community structures in large-scale networks. Phys. Rev. E 76, 036106 (2007)
Liu, X., Murata, T.: Community detection in large-scale bipartite networks. In: Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2009), Washington, DC, pp. 5–8. IEEE Computer Society (2009)
Du, N., Wang, B., Wu, B., et al.: Overlapping community detection in bipartite networks. In: International Conference on IEEE Web Intelligence and Intelligent Agent Technology, 2008, WI-IAT 2008, vol. 1, pp. 176–179. IEEE/WIC/ACM (2008)
Page, L., Brin, S., et al.: The pagerank citation ranking: bringing order to the web. R. Stanford Digital
Richters, O., Peixoto, T.P.: Trust transitivity in social networks. PLoS ONE 6(4), 1–14 (2011)
Yue, Z., Hongli, Z., Weizhe, Z., Junjia, L.: Identifying the influential users in network forum. J. Comput. Res. Dev. 50(10), 2195–2205 (2013)
Yuanzhe, C., Miao, Z., Dijun, L., Chris, D., Sharma, C.: Low-order tensor decompositions for social tagging recommendation. In: Proceedings of the 4th ACM International Conference on Web Search and Data Mining, New York, pp. 695–704 (2011)
Tong, Y., She, J., Chen, L.: Towards better understanding of app functions. J. Comput. Sci. Technol. 30(5), 1130–1140 (2015)
She, J., Tong, Y., Chen, L.: Utility-aware event-participant planning. In: Proceedings of the 34th ACM SIGMOD International Conference on Management of Data (SIGMOD 2015), pp. 1629–1643 (2015)
She, J., Tong, Y., Chen, L., Cao, C.C.: Conflict-aware event-participant arrangement. In: Proceedings of the 31st International Conference on Data Engineering (ICDE 2015), pp. 735–746 (2015)
Newman, M.E.J.: Modularity and community structure in networks. Proc. Nat. Acad. Sci. U.S.A. 103(23), 8577–8582 (2006)
Davis, A., Gardner, B.B., Gardner, M.R.: Deep South. University of Chicago Press, Chicago (1941)
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Chunlong, F., Yan, S., Huimin, S., Guohui, D. (2016). An Improved Community Detection Method in Bipartite Networks. In: Song, S., Tong, Y. (eds) Web-Age Information Management. WAIM 2016. Lecture Notes in Computer Science(), vol 9998. Springer, Cham. https://doi.org/10.1007/978-3-319-47121-1_22
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DOI: https://doi.org/10.1007/978-3-319-47121-1_22
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