基于频繁模式树的约束最大频繁项集挖掘算法OACSCDCSTPCD
Mining Algorithm for Constrained Maximum Frequent Itemsets Based on Frequent Pattern Tree
多数最大频繁项集挖掘算法产生候选项目集的代价很高,而实际应用中用户只关心部分关联规则.针对该问题,提出一种基于频繁模式树的约束最大频繁项集快速挖掘算法.该算法能随时删除不满足约束条件的项集,无需生成候选项目集,由此提高挖掘效率.实验结果证明,该算法的效率优于同类算法.
The cost of producing candidate itemsets is very high in most maximum frequent itemset mining algorithms, but users are often interested in a subset of association rules in practical application, so this paper proposes a mining algorithm for constrained maximum frequent itemsets based on Frequent Pattern tree(FP-tree). It can delete the itemsets which do not meet the constraints at any time and does not produce candidate itemsets, so that the efficienc…查看全部>>
花红娟;张健;陈少华
上海海洋大学信息学院,上海,201306上海海洋大学图书馆,上海,201306上海海洋大学信息学院,上海,201306
信息技术与安全科学
数据挖掘最大频繁项集约束最大频繁项集频繁模式树项约束
data mining maximum frequent itemsets constrained maximum frequent itemsets Frequent Pattern tree(FP-tree) item constraint
《计算机工程》 2011 (9)
78-80,3
国家"863"计划基金资助重点项目"人工鱼礁生态增殖及海域生态调控技术"(2006AA100303)
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