Extraction and Confirmation of Rules for Human Decision Making

Translating knowledge discovered from a database to the form of rule-based representation is a critical step for human decision making. In order to realize such key step, firstly, an approach of using the concept lattice to extract the association rules is proposed. Moreover, the previous extracted rules are integrated with decision maker's subjective preference information to confirm the desirable rules set. Finally, an illustration is presented to demonstrate the above processes in detail.