Application of multidimensional association rules in personal financial services

To better solve the complexity and diversity in personal financial services, we propose a kind of personal financial recommendation system based on association rules. The system makes use of the customers´ financial information to generate data cube, and then generates the recommendation set by multi-dimensional association rule mining. We also propose the concept of recommendation weight and use it for recommending process. As a result of the introduction of multidimensional association rules and the recommendation weight, the recommendations of new service and import service are reasonably managed. This recommendation system is more intelligent, efficient and personalized in solving the complexity and diversity in customizing financial service effectively.