A successful integration of constraint programming and data mining has the potential to lead to
a new ICT paradigm with far reaching implications. It could change the face of data mining and
machine learning as well as constraint programming technology. It would not only allow one to
use data mining techniques in constraint programming to identify and update constraints and
optimization criteria but also to employ constraints and criteria in data mining and machine
learning in order to discover models compatible with prior knowledge. This book reports on some
key results obtained on this integrated and cross- disciplinary approach within the European
FP7 FET Open project no. 284715 on Inductive Constraint Programming and a number of associated
workshops and Dagstuhl seminars. The book is structured in five parts: background learning to
model learning to solve constraint programming for data mining and showcases.
