A Measurement-Theoretic Foundation of Rule Interestingness Evaluation

Abstract

Many measures have been proposed and studied extensively in data mining for evaluating the interestingness (or usefulness) of discovered rules. They are usually defined based on structural characteristics or statistical information about the rules. The meaningfulness of each measure was interpreted based either on intuitive arguments or mathematical properties. There does not exist a framework in which one is able to representthe user judgment explicitly, precisely, and formally. Since the usefulness of discovered rules must be eventually judged by users, a framework that takes user preference or judgment into consideration will be very valuable. The objective of this paper is to propose such a framework based on the notion of user preference. Theresults are useful in establishing a measurement-theoretic foundation of rule interestingness evaluation.