Enhancing Rule Importance Measure Using Concept Hierarchy

Quality issues, measures of interestingness and evaluation of data mining models Workshop

图书情报档案学;计算机科学

Jiye Li ; Nick Cercone ; Serene W. H. Wong ; Lisa Jing Yan

PID  :  84238

来源: CEUR

【 摘 要 】

A rule importance measure is used to evaluate how important are the rules which characterize a data set. This measure was de signed based on association rules and it has been proven to be effective to enumerate the most important rules of all rules generated. However, since rule importance is an objective measure, its usage as a rule interesting ness measure relies on the interpretation of domain experts. We propose to enhance the rule importance measure previously used by incorporat ing a weight biased attribute concept hierarchy. The new measure better reflects the importance of a rule by integrating with the domain knowl edge. A geriatric care data set is used as our experimental data set. We show that this enhanced rule importance measure provides a knowledge