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Mining Negative Association Rules in Multi-database

机译:挖掘多数据库中的负关联规则

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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.
机译:负关联规则(NARS)在物品之间捕获相互排斥的相关性。他们在决策中发挥着重要作用。但是现在,NARS采矿专注于单声道数据库的技术。随着信息和通信技术的快速发展,多数据库挖掘变得越来越重要。在挖掘同时挖掘正和负关联规则时可能会发生数据库内的知识冲突。本文提出了解决冲突的合成相关性与解决多数据库基础上的多数据库中的NAR挖掘冲突和新算法Pnar_mdb。实验结果表明,该算法是正确且有效的。

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