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Comparisons of typical algorithms in negative sequential pattern mining

机译:负序模式挖掘中典型算法的比较

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Negative sequential pattern (NSP), which contains both non-occurring and occurring items, can play more important roles than positive sequential pattern (PSP) in many applications. NSP mining, however, has been just caught attention and very limited methods are available to mine NSP. Furthermore, there is not a unified definition about negative containment, i.e., how a data sequence contains a negative sequence. So in this paper, we select three typical existing methods, PNSP, Neg-GSP and e-NSP, and compare their definitions, runtime and the number of NSPs. Examples and experiments on same dataset clearly show their differences.
机译:负序模式(NSP)包含非出现项和正在发生的项,在许多应用程序中比正序模式(PSP)扮演着更重要的角色。但是,NSP开采只是引起了人们的注意,并且开采NSP的方法非常有限。此外,还没有关于否定包含的统一定义,即数据序列如何包含否定序列。因此,在本文中,我们选择三种典型的现有方法PNSP,Neg-GSP和e-NSP,并比较它们的定义,运行时间和NSP的数量。同一数据集上的示例和实验清楚地表明了它们的差异。

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