Interesting measures for mining association rules

Discovering association rules is one of the most important tasks in data mining and many efficient algorithms were proposed in the literature. However, the number of discovered rules is often so large, so the user cannot analyze all discovered rules. To overcome that problem several methods for mining interesting rules only have been proposed. Many measures have been proposed in the literature to determine the interestingness of the rule. In this paper we have selected a total of eight different measures, we have compared these measures by using a data set, and we have made some recommendation about the use of the measures for discovering the most interesting rules.