One of the strength of our team is to group people working in the field of Machine Learning, Data Mining, NLP and Constraints. This allows to address problems at the intersection of these fields.
For example, in this context of Constraint Programming (CP) and Machine learning/Data mining, we have presented a declarative and generic framework for constrained clustering. Such a framework integrates different kinds of optimization criteria and allows to find a global optimum. Moreover, we show that coupling optimization with some types of constraints allows to handle larger databases and can be interesting for the users. We develop effective dedicated tools in CP solvers to adress these kinds of problem.