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A New Distributed Mining Association Rules Algorithm in Distributed Database System

机译:分布式数据库系统中的一种新的分布式挖掘关联规则算法

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The traditional algorithms create the local candidate sets firstly, and then determine whether the local frequent item sets is the global frequent item sets by the traffic between the nodes. The most different between the proposed algorithm and the traditional algorithms is that it firstly generates all the local frequent item sets at each node and then communicates to the top point. At the top point, there are four cases to deal with all the local frequent item sets. For the fastest case, the determination could be made by the completion of round-trip communications. At the same time, all the operations of this algorithm are completed not by traditional data storage but by a new data storage in which the item is considered as the keyword. The method can save storage space, especially for sparse data. So the support can be calculated by the intersection of the transaction sets, which is much easier than by accessing to the database. Finally, the association rules in the distributed database are mined.
机译:传统算法首先创建本地候选集,然后确定本地频繁项目集是通过节点之间的流量的全局频繁项目集。所提出的算法和传统算法之间的最差异是它首先在每个节点处生成所有本地频繁项目集,然后传送到顶点。在顶点,有四个案例可以处理所有本地频繁项目集。对于最快的情况,可以通过完成往返通信来进行确定。同时,此算法的所有操作都不通过传统数据存储完成,而是通过将项目视为关键字的新数据存储来完成。该方法可以节省存储空间,尤其是稀疏数据。因此,可以通过交易集的交叉来计算支持,这比访问数据库更容易。最后,挖掘了分布式数据库中的关联规则。

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