J. Han and M. Kamber, Data Mining, 2000.
DOI : 10.1145/233269.233324
URL : https://hal.archives-ouvertes.fr/hal-01534761

J. Srivastava, R. Cooley, and M. Deshpande, Web usage mining, ACM SIGKDD Explorations Newsletter, vol.1, issue.2, pp.12-23, 2000.
DOI : 10.1145/846183.846188

T. Hesam, M. Dashti, T. Kloc, G. Lee, T. Michelotti et al., InfoMax gene networks constructed from intervention in the animal models of Parkinson's disease, BMC Neuroscience, vol.8, p.134, 2007.

H. Zheng-zhong and T. Yu-hua, The fuzzy classification and activity prediction of solar active regions, Chinese Astronomy and Astrophysics, vol.27, issue.1, pp.89-93, 2003.
DOI : 10.1016/S0275-1062(03)80010-3

J. Thomas and H. Schulz, Classification of multifluid CP world models, Astronomy & Astrophysics, vol.14, issue.2, pp.395-406, 2001.
DOI : 10.1038/45748

N. Christlieb, L. Wisotzki, and G. Grabhoff, Statistical methods of automatic spectral classification and their application to the Hamburg/ESO Survey, Astronomy & Astrophysics, vol.115, issue.1, pp.397-406, 2002.
DOI : 10.1086/304651

U. Stelzl, U. Worm, M. Lalowski, C. Haenig, F. Brembeck et al., A Human Protein-Protein Interaction Network: A Resource for Annotating the Proteome, Cell, vol.122, issue.6, pp.957-968, 2005.
DOI : 10.1016/j.cell.2005.08.029

L. M. Sarro, J. Debosscher, C. Aerts, and M. López, Comparative clustering analysis of variable stars in the Hipparcos, OGLE Large Magellanic Cloud and CoRoT exoplanet databases. Accepted for publication is, Astronomy and Astrophysics, 2009.

T. Simas, G. Silva, B. Miranda, A. Moitinho, and R. Ribeiro, Knowledge Discovery in Large Data SetsClassification and Discovery in Large Astronomical Surveys, Proceedings of the International Conference, pp.196-200, 2008.

R. A. Peters, A new algorithm for image noise reduction using mathematical morphology, IEEE Transactions on Image Processing, vol.4, issue.5, pp.554-568, 2002.
DOI : 10.1109/83.382491
URL : http://www.vuse.vanderbilt.edu/~rap2/papers/nreduce.ps.Z

J. C. Brailean, R. P. Kleihorst, S. Efstratiadis, A. K. Katsaggelos, and R. L. Lagendijk, Noise reduction filters for dynamic image sequences: a review, Proceedings of the IEEE, pp.1272-1292, 2002.
DOI : 10.1109/5.406412

H. Thomas, C. E. Cormen, R. L. Leiserson, C. Rivest, and . Stein, Introduction to Algorithms Third Edition

I. Soszynski, A. Udalski, M. Szymanski, M. Kubiak, G. Pietrzynski et al., The Optical Gravitational Lensing Experiment. Catalog of RR Lyr Stars in the Large Magellanic Cloud, Acta Astronomica, vol.53, 2003.

D. L. Applegate, R. E. Bixby, V. Chvátal, &. William, and J. Cook, The Traveling Salesman Problem: A Computational Study, 2006.

E. David and . Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, 1989.

E. Montgomery, H. Huang, and A. Assadi, Unsupervised clustering algorithm for N-dimensional data, Journal of Neuroscience Methods, vol.144, issue.1, pp.19-24, 2005.
DOI : 10.1016/j.jneumeth.2004.10.015

E. Montgomery, H. Huang, and A. Assadi, US Patent No: P04257US. New method that allows unsupervised cluster analysis in n-dimensional space, 2005.

E. Montgomery, H. Huang, and A. Assadi, US Patent No: P04257WO. Methods and devices for analysis of clustered data, in particular action potentials (i.e. neuron firing signals in the brain), 2005.