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Hybrid data mining algorithm in cloud computing using MapReduce framework

机译:使用MapReduce框架的云计算中的混合数据挖掘算法

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'Data mining' has transformed into a ubiquitous term in the world of IT and Computer Science in recent times. Developments in this field have been countless. Using one of Apriori algorithm's numerous variants with a couple of insightful additions can significantly improve upon the existing standard of Data Mining. In this paper a new approach to considerably reduce the time complexity of the database scan has been proposed. This has been achieved by using the MapReduce framework for Hadoop Distributed File System (HDFS). Coupled with Cloud computing, which handles large data sets and processing remotely, the resultant system - that uses MapReduce for the full table scan, the Pincer-Search Algorithm, and Cloud Computing - is a force to reckon with.
机译:近年来,“数据挖掘”已转变为IT和计算机科学领域的一个无处不在的术语。在这一领域的发展是无数的。将Apriori算法的众多变体之一与几个有见地的添加结合使用,可以显着改善现有数据挖掘标准。在本文中,已经提出了一种新的方法,可以大大减少数据库扫描的时间复杂度。这是通过使用针对Hadoop分布式文件系统(HDFS)的MapReduce框架实现的。结合使用可处理大型数据集并进行远程处理的云计算,最终系统-使用MapReduce进行全表扫描,Pincer-Search算法和云计算-势不可挡。

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