Mining of Frequent Action Rules

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 base as the search domain for actions, and then propose a strategy based on the FP-Growth algorithm to achieve high performance in action rules extraction. This method was initially tested on real medical diabetic database. The obtained results are quite promising.