RARE: Rare Action Rule Exploration

IEEE BigData(2021)

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摘要
Action rule mining seeks to generate rules that indicate what changes can be made to move an object from one class (state) to another class. An action rule is composed of the changes, known as actions, that correlate with the change in the class value. The current work in action rule mining focuses on frequent, or highly occurring, action rules. The working assumption is that the end user is interested in class transitions that move a large number of objects from the initial class to the new (final) class with a high degree of confidence. Currently, very little work focuses on rare action rules; that is, classes which occur infrequently. In this paper, we provide a definition for a rare action rule and then propose a consequent-constraint based algorithm for generating these rare action rules.
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关键词
Action rule,consequent-constraint,rare mining,action tree,association mining
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