Association rule mining and interestingness measures: A case study

Association Rule Mining is a method which used in data mining. In this method, the objects that are seen together in the data sets are identified and interesting patterns that will help the decision maker are revealed. Revealed associations are expressed in the form of rules. Interestingness measures are used to evaluate the rules. The decision-maker pursues strong and interesting patterns and uses this analysis in the most efficient and correct manner on behalf of the firm. In this study, the interestingness measures which are used in the evaluation of association rules are discussed extensively. In addition, some association rules have been obtained according to some criteria on the data of various stores of a firm and these rules have been evaluated by the interestingness measures. There were different associations in different stores. It can be stated that the findings are useful for the firm's decision makers.