Application of Negative Association Rules in Multi-database

The increasing use of multi-database technology has led to the development of many multi-database systems for real-world application. Large companies may have to confront the multiple data-source problem,so multi-database mining has been an important research area. Negative association rules (NARs) play important roles in decision-making. But nowadays the techniques of NARs mining focus on mono-database. Mining negative association rules in multi-database have not been caused peoplepsilas attention. But NARs in multi-database are very important in real-world applications. Knowledge conflicts within databases may occur when mining both the positive and negative association rules simultaneously. This paper proposed synthesis correlation to resolve conflicts and a new algorithm PNAR_MDB for mining NARs in multi-database on base of previous work on multi-database mining. The experimental results demonstrate that the algorithm is correct and effective.