现代电子技术2007，Vol.30Issue(4)：106-107,110,3.
An Improved Apriori Algorithm
An Improved Apriori Algorithm
LIU Shan 1LIAO Yongyi1
作者信息
- 1. Computer College,CAUC,Tianjin,300300,China
- 折叠
摘要
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 (min_sup=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.关键词
Apriori algorithm/association rules/frequent item-sets/business product/set-treeKey words
Apriori algorithm/association rules/frequent item-sets/business product/set-tree分类
信息技术与安全科学引用本文复制引用
LIU Shan,LIAO Yongyi..An Improved Apriori Algorithm[J].现代电子技术,2007,30(4):106-107,110,3.
