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A New Closed Frequent Itemsets Mining Algorithm Based on GPU

机译:一种基于GPU的新封闭式频繁项目集挖掘算法

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Vertical data format is an important structure in closed frequent itemsets mining. All closed frequent itemsets can be found by simply using the operations of "and" and "or". But it consumes huge amount of storage space, especially in the case of large size data set. This paper proposed an algorithm for mining closed frequent itemsets based on a new data structure deriving from the vertical format. This new data structure can contribute to save storage space by using a multi-layer index. When dealing with large data sets with the acceleration of GPU, this algorithm can obtain a high speed. Our experimental results show that our algorithm uses much less computation time than other similar methods.
机译:垂直数据格式是封闭式频繁项目集的重要结构。只需使用“和”和“或”的操作即可找到所有封闭的频繁项目集。但它消耗了大量的存储空间,特别是在大尺寸数据集的情况下。本文提出了一种基于从垂直格式导出的新数据结构的挖掘频繁项目集的算法。这种新的数据结构可以通过使用多层索引来帮助保存存储空间。在与GPU的加速度处理大数据集时,该算法可以获得高速。我们的实验结果表明,我们的算法使用比其他类似方法的计算时间更少。

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