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首页> 外文期刊>International Journal on Computer Science and Engineering >Frequent Data Itemset Mining Using VS_Apriori Algorithms
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Frequent Data Itemset Mining Using VS_Apriori Algorithms

机译:使用VS_Apriori算法的频繁数据项集挖掘

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The organization, management and accessing of information in better manner in various data warehouse applications have been active areas of research for many researchers for more than last two decades. The work presented in this paper is motivated from their work and inspired to reduce complexity involved in data mining from data warehouse. A new algorithm named VS_Apriori is introduced as the extension of existing Apriori Algorithm that intelligently mines the frequent data itemset in large scale database. Experimental results are presented to illustrate the role of Apriori Algorithm, to demonstrate efficient way and to implement the Algorithm for generating frequent data itemset. Experiments are also performed to show high speedups.
机译:在过去的二十多年中,对于许多研究人员来说,在各种数据仓库应用程序中以更好的方式组织,管理和访问信息一直是研究的活跃领域。本文中介绍的工作源于他们的工作,并启发他们减少从数据仓库进行数据挖掘所涉及的复杂性。作为现有Apriori算法的扩展,引入了一种名为VS_Apriori的新算法,该算法可以智能地挖掘大型数据库中的频繁数据项集。实验结果表明了Apriori算法的作用,证明了有效的方法并实现了生成频繁数据项集的算法。还进行了实验以显示较高的加速比。

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