Selecting a Right Interestingness Measure for Rare Association Rules
Akshat Surana, Rage Uday Kiran, P. Krishna Reddy · Conference on Management of Data · 2010
In the literature, the properties of several interestingness measures have been analyzed and a framework has been proposed for selecting a right interestingness measure for extracting association rules. As rare association rules contain useful knowledge, researchers are making efforts to investigate efficient approaches to extract the same. In this paper, we make an effort to analyze the properties of interestingness measures for determining the interestingness of rare association rules. Based on the analysis, we suggest a set of properties a user should consider while selecting a measure to find the interestingness of rare associations. The experiments on real-world datasets show that the measures that satisfy the suggested properties can determine the interestingness of rare association rules.