Presents advanced tools and techniques available for data and web mining strategies with chapters written by leading world experts. This book provides practicing engineers and scientists with case studies using approaches for data and web mining strategies, and research students with in-depth tutorials on the topics covered.

This book presents research on some of the most recent advances in data mining and knowledge discovery, providing theory as well as its applications on practical real world applications. The methodologies discussed encompass tools like Bayesian networks, and major facets of computational intelligence paradigms. Contributions from top class researchers include: - Recent trends in data mining and knowledge discovery - Advanced data mining techniques in semi-conductor manufacturing - Clustering and visualization in retail markets baskets - Segmentation of continuous data - Instance selection using evolutionary algorithms - Cooperative co-evolution for data mining of Bayesian networks - Knowledge discovery and data mining in medicine - Satellite image classification - Knowledge discovery using rough sets This book presents both practical detail and some of the most up-to-date theory in the field, useful for postgraduates and those who wish to develop applications using advanced data mining and knowledge discovery techniques.

Trends in Data Mining and Knowledge Discovery.- Advanced Methods for the Analysis of Semiconductor Manufacturing Process Data.- Clustering and Visualization of Retail Market Baskets.- Segmentation of Continuous Data Streams Based on a Change Detection Methodology.- Instance Selection Using Evolutionary Algorithms: An Experimental Study.- Using Cooperative Coevolution for Data Mining of Bayesian Networks.- Knowledge Discovery and Data Mining in Medicine.- Satellite Image Classification Using Cascaded Architecture of Neural Fuzzy Network.- Discovery of Positive and Negative Rules from Medical Databases based on Rough Sets.