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References 147<br />

[57] A. S. Rao, M. P. Georgeff, “BDI Agents: From Theory to Practice”, in Proceedings of The<br />

First International Conference on Multi-agent Systems (ICMAS), 1995. pp. 312–319.<br />

[58] G. Dimitrakopoulos, P. Demestichas, W. Koenig, Future Network & Mobile Summit<br />

2010 Conference Proceedings.<br />

[59] John Naisbit and Patricia Aburdene (1991), Megatrends 2000, Avon.<br />

[60] D. C. Luckham, Event Processing for Business: Organizing the Real-Time Enterprise,<br />

John Wiley & Sons, 2012.<br />

[61] T. Mitchell, Machine Learning, McGraw Hill, 1997.<br />

[62] O. Etzion, P. Niblett, Event Processing in Action, Manning, 2011.<br />

[63] V. J. Hodgem, J. Austin, “A Survey of Outlier Detection Methodologies”, Artificial<br />

Intelligence Review, 22(2), pages 85–126, 2004.<br />

[64] F. Angiulli, and C. Pizzuti, “Fast outlier detection in high dimensional spaces” in Proc.<br />

European Conf. on Principles of Knowledge Discovery and Data Mining, 2002.<br />

[65] H. Fan, O. Zaïane, A. Foss, and J. Wu, “Nonparametric outlier detection for efficiently<br />

discovering top-n outliers from engineering data”, in Proc. Pacific-Asia Conf. on Knowledge<br />

Discovery and Data Mining (PAKDD), Singapore, 2006.<br />

[66] A. Ghoting, S. Parthasarathy, and M. Otey, “Fast mining of distance-based outliers in<br />

high dimensional spaces”, in Proc. SIAM Int. Conf. on Data Mining (SDM), Bethesda,<br />

ML, 2006.<br />

[67] G. Box, G. Jenkins, Time Series Analysis: Forecasting and Control, Rev. ed., Oakland,<br />

California: Holden-Day, 1976.<br />

[68] J. Hamilton, Time Series Analysis, Princeton Univ. Press, 1994.<br />

[69] J. Durbin and S.J. Koopman, Time Series Analysis by State Space Methods, Oxford<br />

University Press, 2001.<br />

[70] R. O. Duda, P. E. Hart, D. G. Stork, Pattern Classification, 2nd Edition, Wiley, 2000.<br />

[71] C.M. Bishop, Neural Networks for Pattern Recognition, Oxford University Press, 1995.<br />

[72] C. M. Bishop, Pattern Recognition and Machine Learning, Springer, 2006.<br />

[73] M. J. Zaki, “Generating non-redundant association rules”, Proceedings of the Sixth ACM<br />

SIGKDD International Conference on Knowledge Discovery and Data Mining, 34–43,<br />

2000.<br />

[74] M. J. Zaki, M. Ogihara, “Theoretical foundations of association rules”, 3rd ACM SIG-<br />

MOD Workshop on Research Issues in Data Mining and Knowledge Discovery, 1998.<br />

[75] N. Pasquier, Y. Bastide, R. Taouil, L. Lakhal, “Discovering Frequent Closed Itemsets<br />

for Association Rules”, Proceedings of the 7th International Conference on Database<br />

Theory, (398–416), 1999.<br />

[76] C. M. Kuok, A. Fu, M. H. Wong, “Mining fuzzy association rules in databases”, SIG-<br />

MOD Rec. 27, 1 (March 1998), 41–46.<br />

[77] T. Kohonen, Self-Organizing Maps, Springer, 2001.<br />

[78] S.-H. Hamed, S. Reza, “TASOM: A New Time Adaptive Self-Organizing Map”, IEEE<br />

Transactions on Systems, Man, and Cybernetics—Part B: Cybernetics 33(2): 271–282,<br />

2003,<br />

[79] L.J.P. van der Maaten, G.E. Hinton, “Visualizing High-Dimensional Data Using t-SNE”,<br />

Journal of Machine Learning Research 9(Nov): 2579–2605, 2008.<br />

[80] I. Guyon, S. Gunn, M. Nikravesh, and L. Zadeh (Eds), Feature Extraction, Foundations<br />

and Applications, Springer, 2006.<br />

[81] Y. Bengio, “Learning deep architectures for AI”, Foundations and Trends in Machine<br />

Learning, 2(1):1–12, 2009.

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