Semantics-based classification of rule interestingness measures

Abstract

Assessing rules with interestingness measures is the cornerstone of successful applications of association rule discovery. However, as numerous measures may be found in the literature, choosing the measures to be applied for a given application is a difficult task. In this chapter, the authors present a novel and useful classification of interestingness… (More)

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Cite this paper

@inproceedings{Blanchard2009SemanticsbasedCO, title={Semantics-based classification of rule interestingness measures}, author={Julien Blanchard and Fabrice Guillet and Pascale Kuntz and Yanchang Zhao and Chengqi Zhang and Longbing Cao}, year={2009} }