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Research on FP-Growth algorithm for massive telecommunication network alarm data based on Spark

机译:基于Spark的FP-Growth大规模电信网络告警数据算法研究

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This paper proposes an improved FP-Growth algorithm which modifies the support count to filter high confidence and high lift telecommunication network alarm big data. And to satisfy the big data environment, this paper improves the algorithm to be a distributed algorithm based on Spark. Experiments show that the improved FP-Growth algorithm mining strong association rules either in frequent patterns or non-frequent patterns, and the improved distributed algorithm based on Spark is more efficient in computing than stand-alone and Hadoop mode.
机译:本文提出了一种改进的FP-Growth算法,该算法修改了支持计数以过滤高置信度和高扬程的电信网络警报大数据。为了满足大数据环境的需要,本文将该算法改进为基于Spark的分布式算法。实验表明,改进的FP-Growth算法以频繁模式或非频繁模式挖掘强关联规则,并且基于Spark的改进分布式算法比独立模式和Hadoop模式具有更高的计算效率。

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