By Juan M. Corchado, M. Lourdes Borrajo, María A. Pellicer, J. Carlos Yáñez (auth.), Petra Perner (eds.)
The business convention on information Mining ICDM-Leipzig used to be the fourth assembly in a sequence of annual occasions which began in 2000, geared up through the Institute of computing device imaginative and prescient and utilized desktop Sciences (IBaI) in Leipzig. The undertaking of the convention is to collect researchers and folks from so as to talk about jointly new developments and functions in facts mining. This 12 months a huge spectrum of labor of alternative purposes was once offered starting from photograph mining, drugs and biotechnology, administration and environmental keep watch over, to telecommunications. in addition to that an business exhibition confirmed the profitable program of knowledge mining equipment by means of industries in several components akin to clinical units, mass facts administration platforms, facts mining instruments, and so forth. throughout the dialogue many tasks have been encouraged resulting in new and joint paintings. The fruitful discussions, the alternate of principles and the spirit of the convention made it a awesome occasion for either side, and examine. we want to specific our appreciation to the reviewers for his or her exact and hugely specialist paintings. We take pleasure in the assistance and knowing of the editorial employees at Springer and specifically Alfred Hofmann, who supported the ebook of those court cases within the LNAI sequence. final, yet no longer least, we want to thank all audio system, contributors and business exhibitors who contributed to the luck of the convention. we're watching for welcoming you to ICDM 2005 (www.data-mini- forum.de) and to the recent paintings you'll current there.
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Additional resources for Advances in Data Mining: Applications in Image Mining, Medicine and Biotechnology, Management and Environmental Control, and Telecommunications; 4th Industrial Conference on Data Mining, ICDM 2004, Leipzig, Germany, July 4 -7, 2004, Revised Selected Paper
And Lee D. (1998) The Rectified Gaussian Distribution, Advances in Neural Information Processing Systems, 10. 350 (1998). 4. Fyfe C. (1996) A Neural Network for PCA and Beyond, Neural Processing Letters, 6: 33-41. 5. Oja E. (1989) Neural Networks, Principal Components and Subspaces, International Journal of Neural Systems, 1:61-68. 6. Friedman J. and Tukey J. (1974) A Projection Pursuit Algorithm for Exploratory Data Analysis. IEEE Transaction on Computers, (23): 881-890. 7. Charles D. (1999) Unsupervised Artificial Neural Networks for the Identification of Multiple Causes in Data.
Corchado J. M. and Aiken J. (2002) Hybrid Artificial Intelligence Methods in Oceanographic Forecasting Models. IEEE SMC Transactions Part C. Vol. 4. pp. 307-313. 3. Corchado J. , Corchado E. , Fdez-Riverola F. and Glez-Bedia M. (2003) Maximum Likelihood Hebbian Learning Based Retrieval Method for CBR Systems. 5th International Conference on Case-Based Reasoning, Trondheim, Norway, June 23 to 26, 2003. Springer-Verlag 4. Freedman J. and Tukey J. (1974) A Projection Pursuit Algorithm for Exploratory Data Analysis.
2002) Hybrid Artificial Intelligence Methods in Oceanographic Forecasting Models. IEEE SMC Transactions Part C. Vol. 4. pp. 307-313. nz Abstract. A set of feature descriptors have been proposed and rigorously in the MPEG-7 core experiments. We propose to extend the use of these descriptors onto semantics extraction from images and videos, so as to bridge the semantic gap in content-based image retrieval and enable multimedia data mining on semantics level. A computational framework consisting of a clustering process for feature mapping and a classification process for object extraction is introduced.