Mining Disjunctive Association Rules
نویسندگان
چکیده
Association rule mining is one of the most important and well-researched techniques of data mining, since the seminal papers by R. Agrawal et al. [1, 2]. It aims to induce associations among sets of items in the transaction databases or other data repositories. Ever since, several algorithms for specialized association tasks have appeared: quantitative association rules, generalized association rules, association rules extended with negation, among many other specializations. To the best of our knowledge all these existent approaches that enhance the classic model of association rules do not still cover other important specialized association tasks. In this paper, we propose and justify a model of disjunctive association rules, accompanied by an algorithm that induces rules in accordance with this model. In at least one type of practical application, the algorithm showed that it is efficient and even indispensable: it is the problem of software change impact analysis.
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