About the Book

Contents

Part I. Introduction: 1. Data Mining in a Nutshell 2. Knowledge Discovery in Databases: An Overview 3. Introduction to Inductive Logic Programming 4. Inductive Logic Programming for Knowledge Discovery in Databases Part II. Techniques 5. Three Companions for Data Mining in First Order Logic 6. Inducing Classification and Regression Trees in First Order Logic 7. Relational Rule Induction with CPR0G0L4.4: A Tutorial Introduction 8. Discovery of Relational Association Rules 9. Distance Based Approaches to Relational Learning and Clustering Part III. From Propositional to Relational Data Mining 10. How to Upgrade Propositional Learners to First Order Logic: A Case Study 11. Propositionalization Approaches to Relational Data Mining 12. Relational Learning and Boosting 13. Learning Probabilistic Relational Models Part IV. Applications and Web Resources 14. Relational Data Mining Applications: An Overview 15. Four Suggestions and a Rule Concerning the Application of ILP 16. Internet Resources on ILP for KDD