| An Improved Apriori Algorithm |
| |
| 引用本文： | LIU Shan LIAO Yongyi. An Improved Apriori Algorithm[J]. 现代电子技术, 2007, 30(4): 106-108 |
| |
| 作者姓名： | LIU Shan LIAO Yongyi |
| |
| 作者单位： | Computer College，CAUC，Tianjin，300300，China |
| |
| 摘 要： | 1 IntroductionKnowledge Discoveryin databaseis a newly useinfor-mation availably way that computer automatically pick upuseful information or knowledge fromhuge amounts of da-ta.KDD has been one of research hotspots in the field ofthe data base.Data minin…
|
| 关 键 词： | 数据挖掘 挖掘规则 先验算法 频繁项集 商业产品 |
| 文章编号： | 1004-373X(2007)04-106-02 |
| 修稿时间： | 2006-06-16 |
An Improved Apriori Algorithm |
| |
| LIU Shan,LIAO Yongyi. An Improved Apriori Algorithm[J]. Modern Electronic Technique, 2007, 30(4): 106-108 |
| |
| Authors: | LIU Shan LIAO Yongyi |
| |
| Affiliation: | Computer College,CAUC,Tianjin,300300,China |
| |
| Abstract: | In this paper,We study the Apriori and FP-growth algorithm in mining association rules and give a method for computing all the frequent item-sets in a database.Its basic idea is giving a concept based on the boolean vector business product,which be computed between all the businesses,then we can get all the two frequent item-sets(minsup=2).We basis their inclusive relation to construct a set-tree of item-sets in database transaction,and then traverse path in it and get all the frequent item-sets.Therefore,we can get minimal frequent item sets between transactions and items in the database without scanning the database and iteratively computing in Apriori algorithm. |
| |
| Keywords: | Apriori algorithm association rules frequent item-sets business product set-tree |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
