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文章基本信息

  • 标题:Apriori and Ant Colony Optimization of Association Rules
  • 作者:Anshuman Singh Sadh ; Nitin Shukla
  • 期刊名称:International Journal of Advanced Computer Research
  • 印刷版ISSN:2249-7277
  • 电子版ISSN:2277-7970
  • 出版年度:2013
  • 卷号:3
  • 期号:10
  • 页码:35-42
  • 出版社:Association of Computer Communication Education for National Triumph (ACCENT)
  • 摘要:Association Rule mining is one of the important and most popular data mining technique. Association rule mining can be efficiently used in any decision making processor decision based rule generation. In this paper we present an efficient mining based optimization techniques for rule generation. By using apriori algorithm we find the positive and negative association rules. Then we apply ant colony optimization algorithm (ACO) for optimizing the association rules. Our results show the effectiveness of our approach.
  • 关键词:Association Rule Mining; Positive Association; Negative Association; ACO.
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