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In this paper, we propose a first application of data mining techniques topropositional satisfiability. Our proposed Mining4SAT approach aims to discoverand to exploit hidden structural knowledge for reducing the size ofpropositional formulae in conjunctive normal form (CNF). Mining4SAT combinesboth frequent itemset mining techniques and Tseitin's encoding for a compactrepresentation of CNF formulae. The experiments of our Mining4SAT approach showinteresting reductions of the sizes of many application instances taken fromthe last SAT competitions.

Mining to Compact CNF Propositional Formulae