Generalization of association rules through disjunction

Several efforts were devoted to mining association rules having conjunction of items in premise and conclusion parts. Such rules convey information about the co-occurrence relations between items. However, other links amongst items—like complementary occurrence of items, absence of items, etc.—may occur and offer interesting knowledge to end-users. In this respect, looking for such relationship is a real challenge since not based on the conjunctive patterns. Indeed, catching such links requires obtaining semantically richer association rules, the generalized ones. These latter rules generalize classic ones to also offer disjunction and negation connectors between items, in addition to the conjunctive one. For this purpose, we propose in this paper a complete process for mining generalized association rules starting from an extraction context. Our experimental study stressing on the mining performances as well as the quantitative aspect proves the soundness of our proposal.