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P-tree oriented association rule mining of multiple data sources

机译:面向P树的关联规则挖掘多个数据源

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摘要

A prominent research area in data mining field is (ARM). As distributed databases emerged, need to mine different patterns across them become necessary and hence distributed ARM algorithms were desired. But these algorithms increased communication complexity and overhead. This paper proposes a new algorithm P-tree oriented distributed association rule mining (PDAM) for mining association rules from distributed databases. This algorithm enables a quicker computation of support counts of item sets. P-tree, a special kind of data structure is used in the algorithm which holds the transactional data. These tree data structures do effective storage of data by employing lossless compression techniques. Message exchange optimisation is proposed in this paper. Both the database scans as well as message exchanges are reduced by the proposed method. It would also reduce the size of average transactions, data sets and message exchanges.
机译:数据挖掘领域的一个重要研究领域是(ARM)。随着分布式数据库的出现,有必要在它们之间挖掘不同的模式,因此需要分布式ARM算法。但是这些算法增加了通信的复杂性和开销。提出了一种新的面向P树的分布式关联规则挖掘算法(PDAM),用于从分布式数据库中挖掘关联规则。该算法可以更快地计算项目集的支持计数。 P树是一种特殊的数据结构,用于保存事务数据。这些树数据结构通过采用无损压缩技术来有效地存储数据。本文提出了消息交换优化。所提出的方法减少了数据库扫描和消息交换。它还将减少平均交易,数据集和消息交换的大小。

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