Choosing the right lens: Finding what is interesting in data mining

Abstract

Interestingness measures play an important role in data mining regardless of the kind of patterns being mined. Good measures should select and rank patterns according to their potential interest to the user. Good measures should also reduce the time and space cost of the mining process. This survey reviews the interestingness measures for rules and summaries, classifies them from several perspectives, compares their properties, identifies their roles in the data mining process, and reviews the analysis methods and selection principles for appropriate measures for applications. © Springer-Verlag Berlin Heidelberg 2007.