This is the first textbook on inductive logic programming (ILP) and multi-relational data mining (MRDM). These subfields of data mining and machine learning are concerned with analyzing structured data that arise in numerous applications, such as bioinformatics, Web mining, natural language processing, etc.
The author explains some important techniques in detail by using case studies centered around well-known ILP or MRDM systems. These studies are among the "classics" in the field and they also provide a good starting point for a more general discussion. Related systems and techniques are covered in detailed bibliographies in each chapter.
The book addresses graduate students in computer science, databases and artificial intelligence, as well as practitioners of data mining and machine learning.

Luc De Raedt is currently a full professor (C4) of computer science at the Albert-Ludwigs-University Freiburg and head of the Machine Learning lab. Before coming to Freiburg in 1999, he held positions as (parttime) senior lecturer, lecturer and assistant at the Department of Computer Science of the Katholieke Universiteit Leuven (Belgium) and as post-doc of the Fund for Scientific Research, Flanders. He obtained his undergraduate degree as well as his Ph.D. in computer science from the Katholieke Universiteit Leuven (Belgium) in 1986 and 1991. His Ph.D. thesis was subsequently published by Academic Press.
De Raedt has a rich experience in European Union research projects.´He (co-)coordinated the successful ESPRIT III and IV Inductive Logic Programming (1 and 2) projects, coordinated the IST assessment project APrIL, and the Marie Curie Training Site DAISY (Foundations of Intelligent Systems). He is at present also involved in the European IST-FET project cInQ belonging to FP5.
De Raedt has (co)-organised several international workshops and conferences.