Data Mining and Constraint Programming - Foundations of a Cross-Disciplinary Approach (Paperback, 2016 ed.)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Lecture Notes in Computer Science, 10101
Release date:	December 2016
First published:	2016
Editors:	Christian Bessiere • Luc de Raedt • Lars Kotthoff • Siegfried Nijssen • Barry O'Sullivan • Dino Pedreschi
Dimensions:	235 x 155 x 19mm (L x W x T)
Format:	Paperback
Pages:	349
Edition:	2016 ed.
ISBN-13:	978-3-319-50136-9
Categories:	Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Computing & IT > Applications of computing > Computer modelling & simulation Books > Computing & IT > Applications of computing > Databases > Data mining Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-319-50136-4
Barcode:	9783319501369

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