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基于Fp树的加权频繁模式挖掘算法 被引量：10

Mining Algorithm for Weighted Frequent Pattern Based on Fp Tree
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摘要 提出一种不产生候选项目集的加权频繁模式挖掘算法。对每个项目集权重进行归一化操作,避免加权支持率大于1,证明该算法满足加权向下封闭性。在此基础上,构建基于加权Fp树的剪枝策略。实例分析和实验结果表明,该算法能减少加权频繁项目集生成过程中的计算量,提高加权频繁项目集的生成效率。 This paper presents a new algorithm for mining weighted frequent item sets without generating candidate. A weight set of attributes is normalized to avoid weighted approval rate greater than 1. The new algorithm is testified to satisfy weighted downward closure property. An effectively mining pruning strategy based on weighed Fp-tree is structured. Example analysis and experimental results show that the algorithm can reduce the weighted frequent item sets formation process of computation, and improve weighted frequent item sets generation efficiency.
作者 陈文
机构地区 铜陵学院数学与计算机科学系
出处 《计算机工程》 CAS CSCD 2012年第6期63-65,共3页 Computer Engineering
基金 安徽省高校省级优秀青年人才基金资助项目(2012SQRL191) 安徽省教育厅自然科学基金资助项目(KJ2010B234)
关键词 数据挖掘 关联规则 加权频繁模式 加权Fp树 加权向下封闭性 data mining association rule weighted frequent pattern weighted Fp tree weighted downward closure property
分类号 TP311 [自动化与计算机技术—计算机软件与理论]
  • 相关文献

参考文献6

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二级参考文献17

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共引文献110

同被引文献70

  • 1李云鹏.智能告警专家处理系统在南通电网的应用[J].江苏电机工程,2008,27(5):48-50. 被引量：8
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引证文献10

二级引证文献34

计算机工程
2012年 第6期

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