Prof. Dr. Johannes Fürnkranz is a professor of knowledge engineering at the Technische Universität Darmstadt. He has chaired and served on the boards of the main journals and conferences in this field. His research interests include inductive rule learning, preference learning, game playing, web mining, and data mining in social science.
Dr. Dragan Gamberger heads the Laboratory for Information Systems at the Rudjer Boškovi¿ Institute in Zagreb. He has chaired the main related conference ECML/PKDD, and is a coauthor of the publicly available Data Mining Server. His research interests include data mining and the medical applications of descriptive rule induction.
Prof. Dr. Nada Lavrä heads the Department of Knowledge Technologies at the Jožef Stefan Institute in Ljubljana. She is the author and editor of several books and proceedings in the field of data mining and machine learning, and she has chaired or served on the boards of the main related journals and conferences. Her research interests include machine learning, data mining, and inductive logic programming, and related applications in medicine, public health, bioinformatics, and the management of virtual enterprises. In 1997 she was awarded the Ambassador of Science of Slovenia prize, and in 2007 she was elected as an ECCAI Fellow.

Fills a significant gap in the machine learning literature

Explains the most comprehensive knowledge representation formalism

Offers researchers and graduate students a clear unifying terminology

Includes supplementary material: [...]

Part I. Introduction to Rule Learning.- Machine Learning and Data Mining.- Propositional Rule Learning.- Relational Rule Learning.- Part II. Elements of Rule Learning.- Formal Framework for Rule Analysis.- Features.- Heuristics.- Pruning of Rules and Rule Sets.- Survey of Classification Rule Learning Systems Through the Analysis of Rule Learning Elements Used.- Part III. Selected Topics in Predictive Induction.- Part IV Selected Techniques and Applications.