Guozhu Dong, The University of Melbourne
Jinyan Li, The University of Melbourne
In this paper we will introduce neighborhood-based interestingness by considering unexpectedness in terms of neighborhood-based parameters. We first present some novel notions of distance between rules and of neighborhoods of rules. The neighborhood-based interestingness of a rule is then defined in terms of the pattern of the fluctuation of confidences or the density of mined rules in some of its neighborhoods. Such interestingness can also be defined for sets of rules (e.g. plateaus and ridges) when their neighborhoods have certain properties. We can rank the interesting rules by combining some neighborhood-based characteristics, the support and confidence of the rules, and users' feedback. We discuss how to implement the proposed ideas and compare our work with related ones. We also give a few expected tendencies of changes due to rule structures, which should be taken into account when considering unexpectedness. We concentrate on association rules and briefly discuss generalization to other types of rules.