Discovery Algorithm for Mining both Direct and Indirect Weighted Association Rules

Association rules mining is one of the most important tasks in data mining research. While most of the existing discovery algorithms are focused on mining frequent itemsets, it has been noted recently that some of the infrequent itemsets can provide useful insight view into the data. As a result, indirect association rules have been put forward, the traditional association rules are called direct association rules. However, all the existing indirect association rule mining models assume that all items have the same significance without taking account of their different roles in real world applications. We put forward an indirect weighted association rule mining model to extend the indirect association rule mining model in this paper.