| 本文已被：浏览 5741次 下载 8835次 |
码上扫一扫！ |
|
|
| 基于FP-Tree的最大频繁项目集挖掘及更新算法 |
|
宋余庆1, 朱玉全1,2, 孙志挥1, 陈耿1
|
|
1.东南大学,计算机科学与工程系,江苏,南京,210096;2.河海大学,计算机及信息工程学院,江苏,常州,213022
|
|
| 摘要: |
| 挖掘最大频繁项目集是多种数据挖掘应用中的关键问题,之前的很多研究都是采用Apriori类的候选项目集生成-检验方法.然而,候选项目集产生的代价是很高的,尤其是在存在大量强模式和/或长模式的时候.提出了一种快速的基于频繁模式树(FP-tree)的最大频繁项目集挖掘DMFIA(discover maximum frequent itemsets algorithm)及其更新算法UMFIA(update maximum frequent itemsets algorithm).算法UMFIA将充分利用以前的挖掘结果来减少在更新的数据库中发现新的最大频繁项目集的费用. |
| 关键词: 数据挖掘 最大频繁项目集 关联规则 频繁模式树 增量式更新 |
| DOI： |
| 分类号: |
| 基金项目:Supported by the National Natural Science Foundation of China under Grant No.79970092 (国家自然科学基金); the National Innovation Fund for Small Technology-Based Firms of China under Grant No.00C26213211014 (国家科技型中小企业技术创新基金) |
|
| An Algorithm and Its Updating Algorithm Based on FP-Tree for Mining Maximum Frequent Itemsets |
|
SONG Yu-Qing,ZHU Yu-Quan,SUN Zhi-Hui,CHEN Geng
|
| Abstract: |
| Mining maximum frequent itemsets is a key problem in many data mining application. Most of the previous studies adopt an Apriori-like candidate set generation-and-test approach. However, candidate set generation is still costly, especially when there exist prolific patterns and/or long patterns. In this paper, a fast algorithm DMFIA (discover maximum frequent itemsets algorithm) and its updating algorithm UMFIA (update maximum frequent itemsets algorithm) based on frequent pattern tree (FP-tree) for mining maximum frequent itemsets is proposed. The algorithm UMFIA makes use of previous mining result to cut down the cost of finding new maximum frequent itemsets in an updated database. |
| Key words: data mining maximum frequent itemset association rule frequent pattern tree incremental updating |
