A Novel Approach for Finding Clusters from Complex Networks

Abstract

[1] Zach Solan, David Horn, Eytan Ruppin, Shimon Edelman, “Unsupervised learning of natural languages”, PNAS, vol. 102, no.33, pp. 11629–11634, 2005.
doi:10.1073/pnas.0409746102
PMid:16087885    PMCid:1187953

[2] M. Ester, H.-P. Kriegel, J. Sander, M. Wimmer, X. Xu, “Incremental Clustering for Mining in a Data Warehouse Environment”, In Proceeding of 24th VLDB Conference, 1998.

[3] M. Ester, H.-P. Kriegel, J. Sander, X. Xu, “A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise”, In Proceeding Of KDD, pp.226-231, 1996.

[4] C. Ding, X. He, H. Zha, M. Gu, H. Simon, “A min-max cut algorithm for graph partitioning and data clustering”, In Proceeding of ICDM 2001.

[5] J. Shi, J. Malik, “Normalized cuts and image segmentation”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 8, 2000.

[6] M. E. J. Newman, M. Girvan, “Finding and evaluating community structure in networks”, Phys. Rev. E 69, 026113, 2004.
doi:10.1103/PhysRevE.69.026113

[7] M. E. J. Newman, “Modularity and community structure in networks”, PNAS, vol. 103, no. 23, pp. 8578-8582, 2006.
doi:10.1073/pnas.0601602103
PMid:16723398    PMCid:1482622

[8] A. Clauset, M. E. J. Newman, C. Moore, “Finding community structure in very large networks”, Physical Review E 70, 066111, 2004.
doi:10.1103/PhysRevE.70.066111

[9] R. Guimera, L. A. N. Amaral, “Functional cartography of complex metabolic networks”, Nature, vol. 433, pp.895–900, 2005.
doi:10.1038/nature03288
PMid:15729348    PMCid:2175124

[10] Santo Fortunato, Marc Barthelemy, “Resolution limit in community detection”, PNAS, vol. 104, no.1, pp.36-41, 2007.
doi:10.1073/pnas.0605965104
PMid:17190818    PMCid:1765466

[11] D.M. Chen and X.W. Xu, “An algorithm for identifying useful structure in graphs clustering”, 2010 Second International Workshop on Education Technology and Computer Science, vol. 1, pp. 63-66, Wuhan, China, 2010.
doi:10.1109/ETCS.2010.222

[12] Watts DJ, Strogatz SH. Collective dynamics of 'small-world' networks. Nature, 1998, 393:440-442.
doi:10.1038/30918
PMid:9623998

[13] http://cs.unm.edu/~aaron/research/fastmodularity.htm.

[14] W. W. Zachary. An information flow model for conflict and fission in small groups. Journal of Anthropological Research, 1977, 33: 452-473.

[15] D. Lusseau, K. Schneider, O. J. Boisseau, P. Haase, E. Slooten, S. M. Dawson. The bottlenose dolphin community of Doubtful Sound features a large proportion of long-lasting associations-Can geographic isolation explain this unique trait? Behavioral Ecology and Sociobiology, 2003, 54(4):396-405.
doi:10.1007/s00265-003-0651-y

[16] D. Lusseau. The emergent properties of a dolphin social network. In Proc. R. Soc. London B, 2003 (sup.), 270:186-188.

[17] M. Girvan, M. E. J. Newman. Community structure in social and biological networks. PNAS, 2002, 99(12):7821–7826.
doi:10.1073/pnas.122653799
PMid:12060727    PMCid:122977

[18] A.L. Barabasi, R. Albert, “Emergence of scaling in random networks”, Science, vol. 286, pp.509-512, 1999.
doi:10.1126/science.286.5439.509

[19] X. Xu, N. Yuruk, Z. Feng, T. A. J. Schweiger, “SCAN: A Structural Clustering Algorithm for Networks”, In Proceeding of the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Jose, CA, 2007.

[20] L. Hubert, P. Arabie, “Comparing Partitions. Journal of Classification”, vol. 2, pp.193–218, 1985.
doi:10.1007/BF01908075