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基于向量矩阵的频繁项集挖掘算法 被引量：2

A Frequent Itemsets Mining Algorithm Based on Vector Matrix
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摘要 为减少冗余候选项集的产生,提出了一种基于向量矩阵的频繁项集挖掘算法FIS-Miner.在该算法中,将所有频繁1-项集按支持度升序进行排序并存储其对应的二进制位向量,将这些二进制位向量映射到向量矩阵进行分析找出所有的频繁项集,既实现了数据库的一次扫描又避免了大量候选项集的产生.探讨了该算法的实现步骤,并给出实例验证了该算法的有效性. A new algorithm FIS-Miner （Frequent Item Sets Miner） is presented for discovering frequent item sets to decrease candidate generation based on vector matrix. All frequent 1-itemsets are put into an array in support degree ascending order, storing corresponding binary vector. All frequent item sets are found by analyzing these binary vectors and mapping vector matrix, therefore database needs to scan only one time while avoiding many candidates. This algorithm steps are explored and its validity is examined.
作者 田宏 董爱杰
机构地区 大连交通大学软件学院
出处 《大连交通大学学报》 CAS 2008年第3期74-77,共4页 Journal of Dalian Jiaotong University
关键词 二进制位向量 向量矩阵 频繁项集 最大频繁项集 binary vector vector matrix frequent item sets maximum frequent item sets
分类号 TP311.13 [自动化与计算机技术—计算机软件与理论]
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参考文献5

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共引文献83

同被引文献18

  • 1陈耿,朱玉全,杨鹤标,陆介平,宋余庆,孙志挥.关联规则挖掘中若干关键技术的研究[J].计算机研究与发展,2005,42(10):1785-1789. 被引量：62
  • 2陈晓云,陈袆,王雷,李荣陆,胡运发.基于分类规则树的频繁模式文本分类[J].软件学报,2006,17(5):1017-1025. 被引量：19
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大连交通大学学报
2008年 第3期

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