首页    期刊浏览 2024年09月19日 星期四
登录注册

文章基本信息

  • 标题:Frequent Data Itemset Mining Using VS_Apriori Algorithms
  • 本地全文:下载
  • 作者:N. Badal ; Shruti Tripathi
  • 期刊名称:International Journal on Computer Science and Engineering
  • 印刷版ISSN:2229-5631
  • 电子版ISSN:0975-3397
  • 出版年度:2010
  • 卷号:2
  • 期号:4
  • 页码:1111-1118
  • 出版社:Engg Journals Publications
  • 摘要: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.
  • 关键词:Frequent data itemsets; Apriori.
国家哲学社会科学文献中心版权所有