Distance-based optimization approach for correlation analysis of associ- ation rule mining

A common problem in association rule mining is that a large number of rules are often generated from database.It makes users difficult to analyze and use these rules.To facilitated exploratory analysis,a distance-based optimization approach is used for correlation analysis of association rule mining.The approach mathematically analyzes the value of correlation formulation between correlation rules.Positive and negative rules,as well as other rules can be distinguished and extracted by analyzing the difference of correlation rules.The experiments demonstrate that the proposed approach is effective and credible.