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Infertile couples may benefit from psychiatric evaluation and treatment of both partners.

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Mining association rules may generate a large numbers of rules making the results hard to analyze manually. Pasquier et al. have discussed the generation of GuiguesDuquenne-Luxenburger basis (GD-L basis). Using a similar approach, we introduce a new rule of inference and define the notion of association rules cover as a minimal set of rules that are non-redundant with respect to this new rule of inference. Our experimental results (obtained using both synthetic and real data sets) show that our covers are smaller than the GD-L basis and they are computed in time that is comparable to the classic Apriori algorithm for generating rules.

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