Abstract
Spectral partitioning is a well known method in the area of graph and matrix analysis. Several approaches based on spectral partitioning and spectral clustering were used to detect structures in real world networks and databases. In this paper, we explore two community detection approaches based on the spectral partitioning to analyze a co-authorship network. The partitioning exploits the concepts of algebraic connectivity and characteristic valuation to form components useful for the analysis of relations and communities in real world social networks.
Chapter PDF
References
Bach, F.R., Jordan, M.I.: Learning spectral clustering. In: Thrun, S., Saul, L.K., Schölkopf, B. (eds.) NIPS. MIT Press (2003)
Bühler, T., Hein, M.: Spectral clustering based on the graph p-laplacian. In: Danyluk, A.P., Bottou, L., Littman, M.L. (eds.) ICML. ACM Int. Conf. Proceeding Series, vol. 382, p. 11. ACM (2009)
Ding, C., He, X., Zha, H., Gu, M., Simon, H.: A min-max cut algorithm for graph partitioning and data clustering. In: Proceedings IEEE Int. Conf. on Data Mining, ICDM 2001, pp. 107–114 (2001)
Fiedler, M.: A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory. Czechoslovak Mathematical Journal 25 (1975)
Ghosh, A., Boyd, S.: Growing well-connected graphs. In: 2006 45th IEEE Conference on Decision and Control, pp. 6605–6611. IEEE (2006)
Grady, L., Polimeni, J.R.: Discrete Calculus - Applied Analysis on Graphs for Computational Science. Springer (2010)
Kudělka, M., Horák, Z., Snášel, V., Krömer, P., Platoš, J., Abraham, A.: Social and swarm aspects of co-authorship network. Logic Journal of IGPL Special Issue: HAIS 2010 (2011)
Kurucz, M., Benczur, A., Csalogany, K., Lukacs, L.: Spectral clustering in telephone call graphs. In: Proc. of the 9th WebKDD and 1st SNA-KDD 2007 Workshop on Web Mining and Social Network Analysis, WebKDD/SNA-KDD 2007, pp. 82–91. ACM, New York (2007)
Kurucz, M., Benczúr, A.A., Csalogány, K., Lukács, L.: Spectral Clustering in Social Networks. In: Zhang, H., Spiliopoulou, M., Mobasher, B., Giles, C.L., McCallum, A., Nasraoui, O., Srivastava, J., Yen, J. (eds.) WebKDD 2007. LNCS, vol. 5439, pp. 1–20. Springer, Heidelberg (2009)
Leskovec, J., Lang, K.J., Dasgupta, A., Mahoney, M.W.: Statistical properties of community structure in large social and information networks. In: Proceedings of the 17th Int. Conf. on World Wide Web, WWW 2008, pp. 695–704. ACM, New York (2008)
Luxburg, U.: A tutorial on spectral clustering. Statistics and Computing 17(4), 395–416 (2007)
Mishra, N., Schreiber, R., Stanton, I., Tarjan, R.E.: Clustering Social Networks. In: Bonato, A., Chung, F.R.K. (eds.) WAW 2007. LNCS, vol. 4863, pp. 56–67. Springer, Heidelberg (2007)
Ruan, J., Zhang, W.: An efficient spectral algorithm for network community discovery and its applications to biological and social networks. In: Proceedings of the 2007 Seventh IEEE Int. Conf. on Data Mining, pp. 643–648. IEEE Computer Society, Washington, DC (2007)
Sarkar, S., Soundararajan, P.: Supervised learning of large perceptual organization: graph spectral partitioning and learning automata. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(5), 504–525 (2000)
Shen, X., Papademetris, X., Constable, R.T.: Graph-theory based parcellation of functional subunits in the brain from resting-state fmri data. NeuroImage 50(3), 1027–1035 (2010)
Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(8), 888–905 (2000)
Spielman, D.A., Teng, S.H.: Spectral partitioning works: Planar graphs and finite element meshes. Linear Algebra and its Applications 421(23), 284–305 (2007)
Xu, K.S., Kliger, M., Chen, Y., Woolf, P.J., Hero III, A.O.: Revealing social networks of spammers through spectral clustering. In: Proceedings of the 2009 IEEE International Conference on Communications, ICC 2009, pp. 735–740. IEEE Press, Piscataway (2009)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 IFIP International Federation for Information Processing
About this paper
Cite this paper
Snášel, V., Krömer, P., Platoš, J., Kudělka, M., Horák, Z. (2012). On Spectral Partitioning of Co-authorship Networks. In: Cortesi, A., Chaki, N., Saeed, K., Wierzchoń, S. (eds) Computer Information Systems and Industrial Management. CISIM 2012. Lecture Notes in Computer Science, vol 7564. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33260-9_26
Download citation
DOI: https://doi.org/10.1007/978-3-642-33260-9_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33259-3
Online ISBN: 978-3-642-33260-9
eBook Packages: Computer ScienceComputer Science (R0)