Notice bibliographique
- Notice
Type(s) de contenu et mode(s) de consultation : Texte noté : électronique
Titre(s) : Data Mining and Constraint Programming [Texte électronique] : Foundations of a Cross-Disciplinary Approach / edited by Christian Bessiere, Luc De Raedt, Lars Kotthoff, Siegfried Nijssen, Barry O'Sullivan, Dino Pedreschi
Publication : Cham : Springer International Publishing : Imprint : Springer, 2016
Description matérielle : 1 online resource (XII, 349 pages 73 illustrations)
Collection : Lecture Notes in Computer Science ; 10101
Note(s) : 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
Autre(s) auteur(s) : Bessiere, Christian. Fonction indéterminée
De Raedt, Luc. Fonction indéterminée
Kotthoff, Lars. Fonction indéterminée
Nijssen, Siegfried. Fonction indéterminée
O'Sullivan, Barry. Fonction indéterminée
Pedreschi, Dino (1958-....). Fonction indéterminée
Sujet(s) : Informatique
Algorithmes
Exploration de données
Intelligence artificielle
Simulation par ordinateur
Programmation par contraintes
Indice(s) Dewey :
006.3 (23e éd.) = Intelligence artificielle et calcul naturel
Identifiants, prix et caractéristiques : ISBN 9783319501376
Identifiant de la notice : ark:/12148/cb44681546n
Notice n° :
FRBNF44681546
(notice reprise d'un réservoir extérieur)
Table des matières : Introduction to Combinatorial Optimisation in Numberjack ; Data Mining and Constraints:
An Overview ; New Approaches to Constraint Acquisition ; ModelSeeker: Extracting
Global Constraint Models from Positive Examples ; Learning Constraint Satisfaction
Problems: An ILP Perspective ; Learning Modulo Theories ; Algorithm Selection for
Combinatorial Search Problems: A Survey ; Adapting Consistency in Constraint Solving
; Modeling in MiningZinc ; Partition-Based Clustering Using Constraint Optimisation
; The Inductive Constraint Programming Loop ; ICON Loop Carpooling Show Case ;
ICON Loop Health Show Case ; ICON Loop Energy Show Case.
