Data Mining and Constraint Programming Foundations of a Cross-Disciplinary Approach

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. 

Summary

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. 

Product details

• Assisted by: Dino Pedreschi (Editor), Siegfried Nijssen (Editor), Lars Kotthoff (Editor), Luc De Raedt (Editor), Christian Bessiere (Editor), Lu De Raedt (Editor), Lars Kotthoff et al (Editor), Barry O'Sullivan (Editor)
• Publisher: Springer, Berlin
• Content: Book
• Product form: Paperback / Softback
• Publication date: 01.01.2016
• Subject: Natural sciences, medicine, IT, technology > IT, data processing > IT
• EAN: 9783319501369
• ISBN: 978-3-31-950136-9
• Pages: 349
• Illustrations: XII, 349 p. 73 illus.
• Dimensions (packing): 16.2 x 1.9 x 23.7 cm
• Weight (packing): 552 g
• Series: Lecture Notes in Computer Science > 10101; Lecture Notes in Artificial Intelligence; Lecture Notes in Computer Science; Lecture Notes in Artificial Intelligence
• Subjects: B, Algorithmen und Datenstrukturen, Data Mining, Algorithms, Datenbanken, Artificial Intelligence, angewandte informatik, Computermodellierung und -simulation, Wissensbasierte Systeme, Expertensysteme, computer science, Information Retrieval, Database Management, Information Systems Applications (incl. Internet), Information Systems Applications (incl.Internet), Theory of Computation, Computer and Information Systems Applications, database programming, Application software, Data Mining and Knowledge Discovery, Algorithms & data structures, Internet searching, Algorithm Analysis and Problem Complexity, Computer simulation, Computer modelling & simulation, Simulation and Modeling, Expert systems / knowledge-based systems, Databases, Computer Modelling