| 基于优化的FP-Tree的频繁闭合项集挖掘算法 |
| |
| 引用本文： | 颜伟,苏兆锋,周钦亮. 基于优化的FP-Tree的频繁闭合项集挖掘算法[J]. 曲阜师范大学学报, 2009, 35(2): 57-61 |
| |
| 作者姓名： | 颜伟 苏兆锋 周钦亮 |
| |
| 作者单位： | 曲阜师范大学信息网络中心,273165,曲阜市;鲁东大学管理学院,264025,山东省烟台市;上海市徐汇区漕河泾高新区Mettier,Toledo,200233,上海市 |
| |
| 摘 要： | 在经典的频繁闭合项集挖掘算法中,如Closet与Closet＋,当条件模式数据库很庞大时,频繁项集的数目将会急剧增长,算法的效率会逐步恶化,并且算法挖掘结果的有效性也随着大量冗余模式的产生而下降．本文首先针对传统的FP-tree的算法,给出了一种改进的FP—tree算法,然后在新算法的基础上,提出新的频繁闭合项集挖掘算法,该算法只需把FP-Tree中所有由叶子结点到根结点的路径遍历一遍,就可以得到各项的所有子条件模式基,避免了传统FP-tree算法在同一条路径上向前回溯比较的繁琐．实验表明优化后的算法避免了资源的耗费,减少了频繁闭合项集挖掘的运算开销,大大提高了数据挖掘的效率．
|
| 关 键 词： | 数据挖掘 闭合项集 频繁模式增长 |
Frequent Closed Itemsets Mining Algorithm Based on Improved FP-growth |
| |
| YAN Wei,SU Zhao-feng,ZHOU Qin-liang. Frequent Closed Itemsets Mining Algorithm Based on Improved FP-growth[J]. Journal of Qufu Normal University(Natural Science), 2009, 35(2): 57-61 |
| |
| Authors: | YAN Wei SU Zhao-feng ZHOU Qin-liang |
| |
| Affiliation: | YAN Wei, SU Zhao-feng, ZHOU Qin-liang (1. Information Network Center, Qufu Normal University,273165, Qufu; 2. School of Management, Ludong University, 264025, Yantai, Shandong;3.Mettler-ToIedo Instruments (Shanghai) Co. Ltd, Xuhui rgeion, 200233, Shanghai, PRC) |
| |
| Abstract: | The classic mining algorithms for mining frequent itemsets,such as Closet and Closet+,are proved to be inefficient and produce many redundant patterns.when mining extremely large datasets.This paper gives a new method to improve the performance of FP-tree firstly.Then based on the improved FP-tree a frequent closed itemsets mining algorithm is provided to improve the effectiveness of mining frequent close itemsets.The new algorithm optimizes the process of mining frequent itemsets and does not need to build... |
| |
| Keywords: | data mining closed itemsets FP-growth |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
