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The Research of Web Mining Algorithm Based on Variable Precision Rough Set Model

机译:基于可变精度粗糙集模型的Web挖掘算法研究

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Variable precision rough set model is the extension of rough set model, which introduce theβparameter based on the basic rough set theory, that is. allows a certain degree of miselassification rate existing. This paper presents the web mining algorithm based on variable precision rough set in e-commerce, analyzes the limitation of the reduction methods based on variable precision rough set theory. The experiment shows the CPU Time in the attribute numbers. indicating that VPRS is superior to normal algorithm in web mining in e-commerce. The experiments show the algorithm could flexibly and dynamically web mining and therefore provide a valuable addition to the field.
机译:变精度粗糙集模型是粗糙集模型的扩展,它引入了基于基本粗糙集理论的β参数。允许存在一定程度的误放错误率。本文提出了一种基于可变精度粗糙集的网络挖掘算法,分析了基于可变精度粗糙集理论的约简方法的局限性。实验在属性编号中显示了CPU时间。表示VPRS在电子商务中的网络挖掘中优于常规算法。实验表明,该算法可以灵活,动态地进行Web挖掘,从而为该领域提供了有价值的补充。

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