Data Mining and Knowledge Discovery Handbook, 2 Edition part 55. Knowledge Discovery demonstrates intelligent computing at its best, and is the most desirable and interesting end-product of Information Technology. To be able to discover and to extract knowledge from data is a task that many researchers and practitioners are endeavoring to accomplish. There is a lot of hidden knowledge waiting to be discovered – this is the challenge created by today’s abundance of data. Data Mining and Knowledge Discovery Handbook, 2nd Edition organizes the most current concepts, theories, standards, methodologies, trends, challenges and applications of data mining (DM) and knowledge discovery. | 520 Lior Rokach Rokach L. Maimon O. and Lavi I. Space Decomposition In Data Mining A Clustering Approach Proceedings of the 14th International Symposium On Methodologies For Intelligent Systems Maebashi Japan Lecture Notes in Computer Science Springer-Verlag 2003 pp. 24-31. Rokach L. and Maimon O. and Averbuch M. Information Retrieval System for Medical Narrative Reports Lecture Notes in Artificial intelligence 3055 page 217-228 SpringerVerlag 2004. Rokach L. and Maimon O. and Arbel R. Selective voting-getting more for less in sensor fusion International Journal of Pattern Recognition and Artificial Intelligence 20 3 2006 pp. 329-350. Rokach L. and Maimon O. Theory and applications of attribute decomposition IEEE International Conference on Data Mining IEEE Computer Society Press pp. 473-480 2001. Rokach L. and Maimon O. Feature Set Decomposition for Decision Trees Journal of Intelligent Data Analysis Volume 9 Number 2 2005b pp 131-158. Rokach L. and Maimon O. Clustering methods Data Mining and Knowledge Discovery Handbook pp. 321-352 2005 Springer. Rokach L. and Maimon O. Data mining for improving the quality of manufacturing a feature set decomposition approach Journal of Intelligent Manufacturing 17 3 285-299 2006 Springer. Rokach L. Maimon O. Data Mining with Decision Trees Theory and Applications World Scientific Publishing 2008. E. Shnaider and M. Schneider Fuzzy Tools for Economic Modeling. In Uncertainty Logics Applications in Economics and Management. Proceedings of SIGEF 98 Congress 1988. Shnaider E. M. Schneider and A. Kandel 1997 A Fuzzy Measure for Similarity of Numerical Vectors Fuzzy Economic Review Vol. II No. 1 1997 pp. 17 - Tani T. and Sakoda M. Fuzzy modeling by ID3 algorithm and its application to prediction of heater outlet temperature Proc. IEEE lnternat. Conf. on Fuzzy Systems March 1992 pp. 923-930. Yuan Y. Shaw M. Induction of fuzzy decision trees Fuzzy Sets and Systems 69 1995 125-139. Zimmermann H. J. Fuzzy Set Theory and its Applications
