CoCoMiLe 2014 - Special Issue on Combining Constraint Solving with Mining and Learning

In recent years there is a growing interest in the potential of integrating the field of constraint solving with machine learning and data mining. Until now, these fields have evolved quite independently. Nevertheless, complex mining and learning tasks can often be formalized in terms of constraints that need to be satisfied. This methodology is becoming increasingly compelling, as the community is progressively moving from addressing relatively simple tasks on tabular data to complex problems on structured data. The use of machine learning and data mining techniques to enhance constraint solving is equally promising, and only starting to be explored. Consequently, there is a mutual benefit in the study of these approaches, that can lead to advances in both fields.
This special issue aims to collect relevant contributions on all aspects of the integration of constraint solving with machine learning and data mining. The following is a non-exhaustive list of possible topics:
data mining/machine learning using constraint solving techniques
learning with constraints
constraint-based languages for data mining/machine learning
preference learning for constraint solving
learning and automated constraint modeling/reformulation
constraint acquisition
interactive constraint solving
solver portfolio optimisation
machine learning in search
integrating learning and search
automated parameter optimization / algorithm configuration
Submission information
Please submit your article using the Elsevier Editorial System (http://ees.elsevier.com/artint). To ensure that all manuscripts are correctly identified as submissions for the special issue, select Special Issue - AI, CoCoMiLe when you reach the "Article Type" step in the submission process. Manuscripts can be submitted until the deadline and the reviewing process of each manuscript will start immediately after submission. Preliminary versions of the papers will be published continuously (as soon as accepted) on the special issue website. Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere.
Key dates:
Submissions by Jan 31 2014
First reviews by Mar 31 2014
Revisions by May 31 2014
Notification by June 30 2014
Special issue by end of 2014
For additional information, please contact aij.ccsml.si-AT-gmail.com
The SI Editors: Andrea Passerini (University of Trento, Italy) Tias Guns (K.U. Leuven, Belgium) Remi Coletta (LIRMM, University of Montpellier, France) Guido Tack (Monash University, Australia) Barry O'Sullivan (University College Cork, Ireland)