Abstract
With the social networks getting increasingly larger, fast community detection algorithms like the label propagation algorithm, are attracting more attention. But the label propagation algorithm deals vertices with no proper weight, which leads to the loss in the performance. We propose the connection factor of the vertex to measure its influence on the local connectivity. The connection factor can reveal the topological structure feature, and we propose a unified weight to modify the original label propagation algorithm. Experiments show that our Unified Weighted LPA has an average performance promotion from 5 % to 10 %, in the best case more than 30 %.
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References
Adamic, L.A., Glance, N.: The political blogosphere and the 2004 us election: divided they blog. In: Proceedings of the 3rd International Workshop on Link Discovery, pp. 36–43. ACM (2005)
Hubert, L., Arabie, P.: Comparing partitions. J. Classif. 2(1), 193–218 (1985)
Jeh, G., Widom, J.: Simrank: a measure of structural-context similarity. In: Proceedings of the eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp. 538–543. ACM (2002)
Leskovec, J., Kleinberg, J., Faloutsos, C.: Graph evolution: Densification and shrinking diameters. ACM Trans. Knowl. Discov. Data (TKDD) 1(1), 2 (2007)
Leung, I.X., Hui, P., Lio, P., Crowcroft, J.: Towards real-time community detection in large networks. Phys. Rev. E 79(6), 066107 (2009)
Lusseau, D., Schneider, K., Boisseau, O.J., Haase, P., Slooten, E., Dawson, S.M.: The bottlenose dolphin community of doubtful sound features a large proportion of long-lasting associations. Behav. Ecol. Sociobiol. 54(4), 396–405 (2003)
Mislove, A., Marcon, M., Gummadi, K.P., Druschel, P., Bhattacharjee, B.: Measurement and analysis of online social networks. In: Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement, pp. 29–42. ACM (2007)
Newman, M.E.: Modularity and community structure in networks. Proc. Nat. Acad. Sci. 103(23), 8577–8582 (2006)
Raghavan, U.N., Albert, R., Kumara, S.: Near linear time algorithm to detect community structures in large-scale networks. Phys. Rev. E 76(3), 036106 (2007)
Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 888–905 (2000)
Strehl, A., Ghosh, J.: Cluster ensembles-a knowledge reuse framework for combining multiple partitions. J. Mach. Learn. Res. 3, 583–617 (2002)
Xie, J., Szymanski, B.K.: Labelrank: A stabilized label propagation algorithm for community detection in networks, pp. 138–143 (2013)
Xie, J., Szymanski, B.K., Liu, X.: Slpa: Uncovering overlapping communities in social networks via a speaker-listener interaction dynamic process. In: 2011 IEEE 11th International Conference on Data Mining Workshops, pp. 344–349. IEEE (2011)
Zachary, W.W.: An information flow model for conflict and fission in small groups. J. Anthropol. Res. 33, 452–473 (1977)
Zhang, X., Fei, S., Song, C., Tian, X., Ao, Y.: Label propagation algorithm based on local cycles for community detection. Int. J. Mod. Phys. B 29(5), 112–142 (2015)
Acknowledgement
This research is supported by National High-tech R&D Program of China (863 Program) under Grants 2015AA01A301, by program for New Century Excellent Talents in University’ by National Science Foundation (NSF) China 61272142, 61402492, 61402486, 61379146, 61272483, by the laboratory pre-research fund (9140C810106150C81001).
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Wang, X., Jian, S., Lu, K., Wang, X. (2016). Unified Weighted Label Propagation Algorithm Using Connection Factor. In: Li, J., Li, X., Wang, S., Li, J., Sheng, Q. (eds) Advanced Data Mining and Applications. ADMA 2016. Lecture Notes in Computer Science(), vol 10086. Springer, Cham. https://doi.org/10.1007/978-3-319-49586-6_29
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DOI: https://doi.org/10.1007/978-3-319-49586-6_29
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