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In this paper we propose a satisfiability-based approach for enumerating all frequent, closed and maximal patterns with wild-cards in a given sequence. In this context, since frequency is the most used criterion, we introduce a new polynomial inductive formulation of the cardinality constraint as a Boolean formula. A nogood-based formulation of the(More)
We improve the state-of-the-art in checking the satisfia-bility of large real world qualitative constraint networks (QCNs), by exploiting the loosely connected structure of their underlying graphs. We propose a simple decomposition scheme that retrieves the smaller QCNs that correspond to the biconnected component subgraphs of the underlying graph of a(More)
In this paper, we propose an extension of our Mining for SAT framework to Constraint satisfaction Problem (CSP). We consider n-ary extensional constraints (table constraints). Our approach aims to reduce the size of the CSP by exploiting the structure of the constraints graph and of its associated microstructure. More precisely, we apply itemset mining(More)
In this paper, we propose a first application of data mining techniques to propositional satisfiability. Our proposed mining based compression approach aims to discover and to exploit hidden structural knowledge for reducing the size of propositional formulae in conjunctive normal form (CNF). It combines both frequent itemset mining techniques and Tseitin's(More)