Relational Data Mining Saso Dzeroski and Nada Lavrac, editors Springer, Berlin, 2001 Front matter (foreword by Heikki Mannila , preface) Table of contents (as it appears in the book - PDF, with abstracts - HTML) From the back cover Order this book: from Springer, from Amazon ( .com, .co.uk, .de )

Relational data mining studies methods for knowledge discovery in databases when the database has information about several types of objects. This, of course, is usually the case when the database has more than one table. Hence there is little doubt as to the relevance of the area; indeed, one can wonder why most of data mining research has concentrated on the single table case.

Relational data mining has its roots in inductive logic programming, an area in the intersection of machine learning and programming languages. ... The present book Relational Data Mining provides a thorough overview of different techniques and strategies used in knowledge discovery from multi-relational data. The chapters describe a broad selection of practical inductive logic programming approaches to relational data mining and give a good overview of several interesting applications.

(From the foreword by Heikki Mannila)