Advances in Data Mining: Applications in Image Mining, by Juan M. Corchado, M. Lourdes Borrajo, María A. Pellicer, J.

By Juan M. Corchado, M. Lourdes Borrajo, María A. Pellicer, J. Carlos Yáñez (auth.), Petra Perner (eds.)

The commercial convention on info Mining ICDM-Leipzig used to be the fourth assembly in a chain of annual occasions which begun in 2000, equipped through the Institute of desktop imaginative and prescient and utilized laptop Sciences (IBaI) in Leipzig. The project of the convention is to compile researchers and folks from with the intention to speak about jointly new developments and purposes in facts mining. This 12 months a vast spectrum of labor of other functions used to be provided starting from photo mining, drugs and biotechnology, administration and environmental keep an eye on, to telecommunications. in addition to that an commercial exhibition confirmed the profitable software of information mining tools via industries in several components equivalent to clinical units, mass info administration structures, information mining instruments, and so forth. through the dialogue many initiatives have been encouraged resulting in new and joint paintings. The fruitful discussions, the trade of principles and the spirit of the convention made it a outstanding occasion for each side, and learn. we wish to precise our appreciation to the reviewers for his or her distinctive and hugely expert paintings. We relish the assistance and figuring out of the editorial employees at Springer and specifically Alfred Hofmann, who supported the e-book 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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Extra info 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

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And Fyfe C. (2003) Orientation Selection Using Maximum Likelihood Hebbian Learning, International Journal of Knowledge-Based Intelligent Engineering Systems Volume 7 Number 2, April 2003. Brighton, United Kingdom. 2. 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.

12. : Getting Organization and Human Ready for Information System eChallenges, Vienna (2004). 13. , Methods to Collect and Analyze Organizational Change Management Data: The BEST Approach, Colloquium of the Haifa University research Center of Organizational Behavior HR Management, 24/3/2004 14. : Defining Similarity Measures: Top-Down vs. ), ECCBR2002, (2002) 406-420. 15. : Pattern Classification and Scene Analysis, Wiley, New-York, (1973). 16. : Features of Similarity, Psychological Review 84 (4), (1977), 327-352.

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. IEEE Transaction on Computers, (23): 881-890, 1974. 5. Fyfe C. and Corchado J. M. (2001) Automating the construction of CBR Systems using Kernel Methods.

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