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Interestingness Of Discovered Association Rules In Terms Of Neighborhood-Based Unexpectedness, Guozhu Dong, Jinyan Li

Kno.e.sis Publications

One of the central problems in knowledge discovery is the development of good measures of interestingness of discovered patterns. With such measures, a user needs to manually examine only the more interesting rules, instead of each of a large number of mined rules. Previous proposals of such measures include rule templates, minimal rule cover, actionability, and unexpectedness in the statistical sense or against user beliefs.

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 neighborhood of rules. The neighborhood-based interestingness of …