Data Mining and Computational Intelligence

The volume offers a comprehensive coverage of the recent advances in the application of soft computing and fuzzy logic theory to data mining and knowledge discovery databases. It focuses on some of the hardest, and yet unsolved, issues of data mining like understandability of patterns, finding complex relationships between attributes, handling missing and noisy data, mining very large datasets, change detection in time series, and integration of the discovery process with database management systems.

Data Mining with Neuro-Fuzzy Models.- Granular Computing in Data Mining.- Fuzzification and Reduction of Information - Theoretic Rule Sets.- Mining Fuzzy Association Rules in a Database Containing Relational and Transactional Data.- Fuzzy Linguistics Summaries via Association Rules.- The Fuzzy-ROSA Method: A Statistically Motivated Fuzzy Approach for Data-Based Generation of Small Interpretable Rule Bases in High-Dimensional Search Spaces.- Discovering Knowledge from Fuzzy Concept Lattice.- Mining of Labeled Incomplete Data Using Fast Dimension Partitioning.- Mining a Growing Feature Map by Data Skeleton Modelling.- Soft Regression - A Data Mining Tool.- Some Practical Applications of Soft Computing and Data Mining.- Intelligent Mining in Image Databases, with Applications to Satellite Imaging and to Web Search.- Fuzzy Genetic Modeling and Forecasting for Nonlinear Time Series.