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  • 标题:Implementing Improved Algorithm Over APRIORI Data Mining Association Rule Algorithm
  • 本地全文:下载
  • 作者:Sanjeev Rao ; Priyanka Gupta
  • 期刊名称:International Journal of Computer Science & Technology
  • 印刷版ISSN:2229-4333
  • 电子版ISSN:0976-8491
  • 出版年度:2012
  • 卷号:3
  • 期号:1
  • 页码:489-493
  • 语种:English
  • 出版社:Ayushmaan Technologies
  • 摘要:In this paper we present new scheme for extracting associationrules that considers the time, number of database scans, memoryconsumption, and the interestingness of the rules. Discover a FISdata mining association algorithm that removes the disadvantagesof APRIORI algorithm and is effcient in terms of number ofdatabase scan and time. The frequent patterns algorithm withoutcandidate generation eliminates the costly candidate generation.It also avoids scanning the database again and again. So, weuse Frequent Pattern (FP) Growth ARM algorithm that is moreeffcient structure to mine patterns when database grows.
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