Abstract
Declarative pattern mining implies to define common frameworks and atomic operators for different problems. In this paper, we consider Inclusion Dependency (IND) mining which is a classical data mining problem, with many applications in databases and data analysis. We present a novel and quite surprising result: IND mining can be optimized by a closure operator, as it is done for support-based pattern mining. As a consequence, and through a data pre-processing, satisfied closed INDs can be mined with very few programming efforts, using closed item set mining procedure as a basic operator.
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