Abstract
In this paper, we described a technique for identifying and presenting frequent pattern migrations in temporal network data. The migrations are identified using the concept of a Migration Matrix and presented using a visualisation tool. The technique has been built into the Pattern Migration Identification and Visualisation (PMIV) framework which is designed to operate using trend clusters which have been extracted from “big” network data using a Self Organising Map technique.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Nohuddin, P.N.E., Christley, R., Coenen, F., Setzkorn, C.: Trend Mining in Social Networks: A Study Using a Large Cattle Movement Database. In: Perner, P. (ed.) ICDM 2010. LNCS (LNAI), vol. 6171, pp. 464–475. Springer, Heidelberg (2010)
Nohuddin, P.N.E., Coenen, F., Christley, R., Setzkorn, C.: Detecting Temporal Pattern and Cluster Changes in Social Networks: A Study Focusing UK Cattle Movement Database. In: Shi, Z., Vadera, S., Aamodt, A., Leake, D. (eds.) IIP 2010. IFIP AICT, vol. 340, pp. 163–172. Springer, Heidelberg (2010)
Kohonen, T.: The Self Organizing Maps. Series in Information Sciences, vol. 30. Springer, Heidelberg (1995)
Kohonen, T.: The Self Organizing Maps. Neurocomputing Elsevier Science 21, 1–6 (1998)
Sugiyama, K., Misue, K.: Graph Drawing by the Magnetic Spring Model. Journal of Visual Languages and Computing 6(3), 217–231 (1995)
Hido, S., Idé, T., Kashima, H., Kubo, H., Matsuzawa, H.: Unsupervised Change Analysis Using Supervised Learning. In: Washio, T., Suzuki, E., Ting, K.M., Inokuchi, A. (eds.) PAKDD 2008. LNCS (LNAI), vol. 5012, pp. 148–159. Springer, Heidelberg (2008)
Newman, M.E.J.: Fast Algorithms for Detecting Community Structure in Networks. Journal of Physical Review E, 1-5 (2004)
Nohuddin, P.N.E., Sunayama, W., Christley, R., Coenen, F., Setzkorn, C.: Trend Mining and Visualisation in Social Networks. In: Proc. of the 31st SGAI International Conference on Artificial Intelligence (2012)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Nohuddin, P.N.E., Coenen, F., Christley, R., Sunayama, W. (2012). Identification and Visualisation of Pattern Migrations in Big Network Data. In: Anthony, P., Ishizuka, M., Lukose, D. (eds) PRICAI 2012: Trends in Artificial Intelligence. PRICAI 2012. Lecture Notes in Computer Science(), vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_91
Download citation
DOI: https://doi.org/10.1007/978-3-642-32695-0_91
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32694-3
Online ISBN: 978-3-642-32695-0
eBook Packages: Computer ScienceComputer Science (R0)