Data Mining and Constraint Programming

Christian Bessiere

ISBN 10: 3319501364 / ISBN 13: 9783319501369

Published by Springer International Publishing, Springer International Publishing Dez 2016, 2016

About this Item

Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 364 pp. Englisch.

Seller Inventory # 9783319501369

Bibliographic Details

• Title: Data Mining and Constraint Programming
• Publisher: Springer International Publishing, Springer International Publishing Dez 2016
• Publication Date: 2016
• Language: English
• ISBN 10: 3319501364
• ISBN 13: 9783319501369
• Binding: Taschenbuch
• Condition: Neu

About this title

Synopsis

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.