Data Mining and Knowledge Discovery Handbook, 2 Edition part 47

Data Mining and Knowledge Discovery Handbook, 2 Edition part 47. 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. | 440 G. Peter Zhang Dai Y. Nakano Y. 1998 Recognition of facial images with low resolution using a Hopfield memory model. Pattern Recognition 31 159-167. Dasu T. Johnson T. 2003 Exploratory Data Mining and Data Cleaning. New Jersey Wiley. De Groot D. Wurtz D. 1991 Analysis of univariate time series with connectionist nets A case study of two classical examples. Neurocomputing 3 177-192. Deboeck G. Kohonen T. 1998 Visual Explorations in Finance with Self-organizing Maps. London Springer-Verlag. Delen D. Sharda R. Bessonov M. 2006 Identifying significant predictors of injury severity in traffic accidents using a series of artificial neural networks Accident Analysis and Prevention 38 434-444. Dhar V. Chou D. 2001 A comparison of nonlinear methods for predicting earnings surprises and returns. IEEE Transactions on Neural Networks 12 907-921. Dia H. 2001 An object-oriented neural network approach to short-term traffic forecasting. European Journal of Operation Research 131 253-261. Dittenbach M. Rauber A. Merkl D. 2002 Uncovering hierarchical structure in data using the growing hierarchical self-organizing map. Neurocompuing 48 199-216. Doganis P. Alexandridis A. Patrinos P. Sarimveis H. 2006 Time series sales forecasting for short shelf-life food products based on artificial neural networks and evolutionary computing. Journal of Food Engineering 75 196-204. Dutot . Rynkiewicz J. Steiner . Rude J. 2007 A 24-h forecast of ozone peaks and exceedance levels using neural classifiers and weather predictions Modelling and Software 22 1261-1269. Dutta S. Shenkar S. 1993 Bond rating a non-conservative application of neural networks. In Neural Networks in Finance and Investing Trippi R. and Turban E. eds. Chicago Probus Publishing Company. Enke D. Thawornwong S. 2005 The use of data mining and neural networks for forecasting stock market returns. Expert Systems with Applications 29 927-940. Evans . 1997 Discovering associations in retail transactions using neural .