An optimization of data mining algorithms used in fuzzy association rules

Abstract

The research areas on this topic have been considerably extended since the first seminal paper on data mining. Fuzzy logic plays an important role in certain aspects of data mining applications such as fuzzy clustering, discovery of fuzzy association rules, and so on. Unlike a set of crisp association rules, fuzzy association rules can create a combinatorial explosion of association rules that map linguistic data to numerical values. In this paper we propose a simple technique for limiting the creation of fuzzy association rules. In addition, the computational efficiency can be improved pruning unnecessary rules.