FAARM: Frequent Association Action Rules Mining Using FP-Tree

Action rules mining aims to provide recommendations to analysts seeking to achieve a specific change. An action rule is constructed as a series of changes, or actions, which can be made to some of the flexible characteristics of the information system that ultimately triggers a change in the targeted attribute. The existing action rules discovery methods consider the input decision system as their search domain and are limited to expensive and ambiguous strategies. In this paper, we define and propose the notion of action table as the ideal search domain for actions, and then propose a strategy based on the FP-Tree structure to achieve high performance in rules extraction.