Relational Data Mining - Table of Contents

Table of Contents

Part I. Introduction

1.	Data Mining in a Nutshell
	Saso Dzeroski

2.	Knowledge Discovery in Databases: An Overview
	Usama Fayyad

3.	An Introduction to Inductive Logic Programming
	Saso Dzeroski and Nada Lavrac

4.	Inductive Logic Programming for Knowledge Discovery in Databases
	Stefan Wrobel

Part II. Techniques

5.	Three Companions for Data Mining in First Order Logic
	Luc De Raedt, Hendrik Blockeel, Luc Dehaspe, and Wim Van Laer

6.	Inducing Classification and Regression Trees in First Order Logic
	Stefan Kramer and Gerhard Widmer

7.	Relational Rule Induction with CProgol4.4: A Tutorial Introduction
	Stephen Muggleton and John Firth

8.	Discovery of Relational Association Rules
	Luc Dehaspe and Hannu Toivonen

9.	Distance Based Approaches to Relational Learning and Clustering
	Mathias Kirsten, Stefan Wrobel, and Tamas Horvath

Part III. From Propositional to Relational Data Mining

10.	How to Upgrade Propositional Learners to First Order Logic: A Case Study
	Wim Van Laer and Luc De Raedt

11.	Propositionalization Approaches to Relational Data Mining
	Stefan Kramer, Nada Lavrac, and Peter Flach

12.	Relational Learning and Boosting
	Ross Quinlan

13.	Learning Probabilistic Relational Models
	Lise Getoor, Nir Friedman, Daphne Koller, and Avi Pfeffer

Part IV. Applications and Web Resources

14.	Relational Data Mining Applications: An Overview
	Saso Dzeroski

15.	Four Suggestions and a Rule Concerning the Application of ILP
	Ashwin Srinivasan

16.	Internet Resources on ILP for KDD
	Ljupco Todorovski, Irene Weber, Nada Lavrac, Olga Stepankova, Saso Dzeroski, Dimitar Kazakov, Darko Zupanic, and Peter Flach