A Common Logic Approach to Data Mining and Pattern Recognition -- The One Clause at a Time (OCAT) Approach to Data Mining and Knowledge Discovery -- An Incremental Learning Algorithm for Inferring Logical Rules from Examples in the Framework of the Common Reasoning Process -- Discovering Rules That Govern Monotone Phenomena -- Learning Logic Formulas and Related Error Distributions -- Feature Selection for Data Mining -- Transformation of Rational Data and Set Data to Logic Data -- Data Farming: Concepts and Methods -- Rule Induction Through Discrete Support Vector Decision Trees -- Multi-Attribute Decision Trees and Decision Rules -- Knowledge Acquisition and Uncertainty in Fault Diagnosis: A Rough Sets Perspective -- Discovering Knowledge Nuggets with a Genetic Algorithm -- Diversity Mechanisms in Pitt-Style Evolutionary Classifier Systems -- Fuzzy Logic in Discovering Association Rules: An Overview -- Mining Human Interpretable Knowledge with Fuzzy Modeling Methods: An Overview -- Data Mining from Multimedia Patient Records -- Learning to Find Context Based Spelling Errors -- Induction and Inference with Fuzzy Rules for Textual Information Retrieval -- Statistical Rule Induction in the Presence of Prior Information: The Bayesian Record Linkage Problem -- Some Future Trends in Data Mining.