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MAXFP-Miner:利用FP-tree快速挖掘最大频繁项集 被引量：4

MAXFP-Miner: Mining Maximal Frequent Itemsets Efficiently by Using FP-tree
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摘要 为提高频繁项集的挖掘效率,提出了最大频繁项集树的概念和基于FP-tree的最大频繁项集挖掘算法MAXFP-Miner.首先建立了FP-tree,在此基础上建立最大频繁项集树MAXFP-tree,MAXFP-tree中包含了所有最大频繁项集,缩小了搜索空间,提高了算法的效率.算法分析和实验表明,该算法特别适合于挖掘稠密型及具有长频繁项集的数据集. In order to improve the efficiency of mining frequent itemsets, the concept of maximal frequent itemset tree and an efficient algorithm, MAXFP-Miner, based on FP-tree for mining maximal frequent itemsets are proposed. After the FP-tree is created , a maximal frequent itemset tree, MAXFP-tree, is built up to store all the maximal frequent itemsets. Therefore, this MAXFP-tree reduces the search space and improves the efficiency of the algorithm. The analysis on the algorithm and the results of experiment show that the algorithm is especially effective for mining dense datasets with long frequent itemsets.
作者 陈慧萍 王建东 叶飞跃
机构地区 南京航空航天大学信息科学与技术学院
出处 《控制与决策》 EI CSCD 北大核心 2005年第8期887-891,共5页 Control and Decision
基金 国家973计划项目(G1999032701) 江苏省自然科学基金项目(BK2002091)
关键词 数据挖掘 FP-TREE 频繁项集 MAXFP-tree Data mining FP-tree Frequent itemset MAXFP-tree
分类号 TP311 [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10

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二级参考文献9

  • 1[1]Agrawal R, Imielinski T, Swami A. Mining association rules between sets of items in large databases. In: Proceedings of ACM SIGMOD International Conference on Management of Date, Washington DC, 1993.207～216
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控制与决策
2005年 第8期

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