Users are faced with the task of selecting the pieces of knowledge which is the highest quality or interest according to his preferences. Because the selection is sometimes a daunting task, designing quality and interestingness measures has become an important challenge for data mining researchers in the last decade. This book presents the state of the art concerning quality and interestingness measures for data mining. The chapters include surveys, comparative studies of existing measures, the proposed new measures, simulations, and case studies.