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EFP-M2: Efficient Model for Mining Frequent Patterns in Transactional Database

机译:EFP-M2:用于在事务数据库中挖掘频繁模式的有效模型

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Discovering frequent patterns plays an essential role in many data mining applications The aim of frequent patterns is to obtain the information about the most common patterns that appeared together. However, designing an efficient model to mine these patterns is still demanding due to the capacity of current database size. Therefore, we propose an Efficient Frequent Pattern Mining Model (EFP-M2) to mine the frequent patterns in timely manner. The result shows that the algorithm in EFP-M21 is outperformed at least at 2 orders of magnitudes against the benehmarked FP-Growth.
机译:发现频繁模式在许多数据挖掘应用程序中起着至关重要的作用。频繁模式的目的是获得有关一起出现的最常见模式的信息。但是,由于当前数据库大小的容量,仍然需要设计一种有效的模型来挖掘这些模式。因此,我们提出了一种有效的频繁模式挖掘模型(EFP-M2)来及时挖掘频繁模式。结果表明,EFP-M21中的算法相对于标记为FP-Growth的算法至少要好2个数量级。

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