Data Mining and Constraint Programming
Foundations of a Cross-Disciplinary Approach
Editors: Bessiere, C., De Raedt, L., Kotthoff, L., Nijssen, S., O'Sullivan, B., Pedreschi, D. (Eds.)
Free Preview- Reports on key results obtained in the field of data mining and constraint programming
- Integrated and cross-disciplinary approach
- Features state-of-the art research
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- About this book
-
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.
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Data Mining and Constraint Programming
- Book Subtitle
- Foundations of a Cross-Disciplinary Approach
- Editors
-
- Christian Bessiere
- Luc De Raedt
- Lars Kotthoff
- Siegfried Nijssen
- Barry O'Sullivan
- Dino Pedreschi
- Series Title
- Lecture Notes in Artificial Intelligence
- Series Volume
- 10101
- Copyright
- 2016
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG
- eBook ISBN
- 978-3-319-50137-6
- DOI
- 10.1007/978-3-319-50137-6
- Softcover ISBN
- 978-3-319-50136-9
- Edition Number
- 1
- Number of Pages
- XII, 349
- Number of Illustrations
- 73 b/w illustrations
- Topics
