The rough set approach to association rule mining

In transaction processing, an association is said to exist between two sets of items when a transaction containing one set is likely to also contain the other. In information retrieval, an association between two sets of keywords occurs when they cooccur in a document. Similarly, in data mining, an association occurs when one attribute set occurs together with another. As the number of such associations may be large, maximal association rules are sought, e.g., Feldman et al. (1997, 1998). Rough set theory is a successful tool for data mining. By using this theory, rules similar to maximal associations can be found. However, we show that the rough set approach to discovering knowledge is much simpler than the maximal association method.