Mining of association rules is one of the most adopted techniques for data mining in the most widespread application domains. A great deal of work has been carried out in the last years on the development of efficient algorithms for association rules extraction. Indeed, this problem is a computationally difficult task, known as NP-hard (Calders, 2004), which has been augmented by the fact that normally association rules are being extracted from very large databases. Moreover, in order to increase the relevance and interestingness of obtained results and to reduce the volume of the overall result, constraints on association rules are introduced and must be evaluated (Ng et al.,1998; Srikant et al., 1997). However, in this contribution, we do not focus on the problem of developing efficient algorithms but on the semantic problem behind the extraction of association rules (see Tsur et al. [1998] for an interesting generalization of this problem).
Optimization of Association Rules Extraction Through Exploitation of Context Dependent Constraints
