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  • 标题:Performance Enhancement of Association Rule Mining Based Apriori Algorithm
  • 本地全文:下载
  • 作者:Sachin Saxena ; Brij Mohan
  • 期刊名称:International Journal of Advanced Research In Computer Science and Software Engineering
  • 印刷版ISSN:2277-6451
  • 电子版ISSN:2277-128X
  • 出版年度:2013
  • 卷号:3
  • 期号:8
  • 出版社:S.S. Mishra
  • 摘要:In the past decade, a significant amount of research was devoted to develop to analyze volumes of data mechanically in an efficient and effective way so that the users don't have to look through that massive amount of data manually for generating various association rules among them. Apriori algorithm, which is the most famous and commonly used data mining algorithm. In this manuscript an attempt has been made by proposing an improvement of the performance of the Apriori algorithm in such a way that when we will implement on a large records, it will lead to less time consuming and fast implementation for generating frequent itemsets
  • 关键词:Apriori algorithm; Association rule mining; frequent itemsets; Signature algorithm
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