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计算机工程 ›› 2009, Vol. 35 ›› Issue (15): 97-99,1. doi: 10.3969/j.issn.1000-3428.2009.15.033

• 软件技术与数据库 • 上一篇    下一篇

基于事务树的最大频繁项集挖掘算法

张忠平,郑为夷   

  1. (燕山大学信息科学与工程学院,秦皇岛 066004)
  • 收稿日期:1900-01-01 修回日期:1900-01-01 出版日期:2009-08-05 发布日期:2009-08-05

Maximal Frequent Itemsets Mining Algorithm Based on Transaction Tree

ZHANG Zhong-ping, ZHENG Wei-yi   

  1. (College of Information Science and Engineering, Yanshan University, Qinhuangdao 066004)
  • Received:1900-01-01 Revised:1900-01-01 Online:2009-08-05 Published:2009-08-05

摘要: 针对Apriori算法在寻找频繁项集的过程中需多次扫描数据库、侯选项集过多、支持度计算过于复杂等问题,提出TT-Apriori算法。该算法将事务数据库转化成事务树,通过遍历事务树能直接快速地找到最大频繁项目集。简化支持度的计算,避免对整个数据库的扫描和大量的连接步骤,从而提高挖掘效率。

关键词: 最大频繁项集, TT-Apriori算法, 事务树, 向量内积

Abstract: Aiming at the shortage of Apriori algorithm in find of frequent items such as numerous search-designate database set too many times and gennerate too many candidate itemsets, this paper proposes the TT-Apriori algorithm. This algorithm maps the tings-datebase into transaction-tree. Using the transaction tree can quickly find the maximal frequent itemsets. In the meamwhile it can simplify the calculation of support and avoid the scanning of the entire database and a large number of connecting steps to improve the efficiency of the mining.

Key words: maximal frequent itemsets, TT-Apriori algorithm, transaction tree, vector in plot

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