Average Distance Based Method for Association Rules Discovery in Relational Databases

Data mining, association rule, categorical attribute, quantitative attribute, average distance

The paper describes the new method for association rule discovery in relational databases, which contain quantitative and categorical attributes. Many methods have been developed yet. But most of these methods are based on initial equi-depth discretization of quantitative attributes. These approaches bring the loss of information. The basic idea of the new method is to separate processing of categorical and quantitative attributes. The first step finds frequent k-itemsets containing only values of categorical attributes and then quantitative attributes are processed one by one. Discretization of values during quantitative attributes processing is based on a new measure called average distance.