Mining Positive and Negative Association Rules in Multi-database Based on Minimum Interestingness

With the increasing development and application of information and communication technologies, multi-database mining is becoming more and more important. Association rules mining is the major topic in multi-database. According to Piatetsky-Shapiropsilas argument, an association rule is interesting only if the rule meets the minimum interestingness condition. In this paper, we extended this condition to mine association rules in multi-database and improved it to check the correlation of association rules. An algorithm PNAR_MDB _on P-S measure is proposed and the experimental results demonstrated the algorithm is effective.