"This book will give the reader a perspective into the core theory and practice of data mining and knowledge discovery (DM&KD). Its chapters combine many theoretical foundations for various DM&KD methods, and they present an array of examples - many of which are drawn from real-life applications. Most of the theoretical developments discussed are accompanied by an extensive empirical analysis, which should give the reader both a deep theoretical and practical insight into the subjects covered." The intended audience for this book includes graduate students studying data mining who have some background in mathematical logic and discrete optimization as well as researchers and practitioners in the same area.