Extending the UML for Designing Association Rule Mining Models for Data Warehouses

Association rules (AR) are one of the most popular data mining techniques in searching databases for frequently occurring patterns. In this paper, we present a novel approach to accomplish the conceptual design of data warehouses together with data mining association rules, allowing us to implement the association rules defined in the conceptual modeling phase. The great advantage of our approach is that the association rules are specified from the early stages of a data warehouse project and based on the main final user requirements and data warehouse goals, instead of specifying them on the final database implementation structures such as tables, rows or columns. Finally, to show the benefit of our approach we implement the specified association rules on a commercial data warehouse management server.