Mining Negative Association Rules in Multi-database

Negative association rules (NARs) catch mutually exclusive correlations among items. They play important roles in decision-making. But nowadays the techniques of NARs mining focus on mono-database. With the rapid development of information and communication technologies, multi-database mining is becoming more and more important. 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.