|
|||||
|
|
| A Depth-first Algorithm of Finding All Association Rules Generated by a Frequent Itemset | |
| 作者姓名： | 武坤 姜保庆 魏庆 |
| 作者单位： | [1]Institute of Data and Knowledge Engineering, Henan University, Kaifeng 475001 [2]The Personnel Department, Zhengzhou Institute of Aeronautical Industry Management ,Zhengzhou 450000 [3]The Computer Science Department, Henan University of Finance and Economics, Zhengzhou 450000 |
| 基金项目： | 国家自然科学基金;河南省自然科学基金 |
| 摘 要： | The classical algorithm of finding association rules generated by a frequent itemset has to generate all nonempty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed an improved algorithm. The algorithm finds all consequents layer by layer, so it is breadth-first. In this paper, we propose a new algorithm Generate Rules by using Set-Enumeration Tree （GRSET） which uses the structure of Set-Enumeration Tree and depth-first method to find all consequents of the association rules one by one and get all association rules correspond to the consequents.Experiments show GRSET algorithm to be practicable and efficient. |
| 关 键 词： | 计算方法 项集 深度优先算法 广度优先算法 |
| 收稿时间： | 2006-08-20 |
| 修稿时间： | 2006-08-20 |
A Depth-first Algorithm of Finding All Association Rules Generated by a Frequent Itemset |
|
| WU Kun,JIANG Bao-qing,WEI Qing.A Depth-first Algorithm of Finding All Association Rules Generated by a Frequent Itemset[J].Journal of Donghua University,2006,23(6):1-4,9. | |
| Authors: | WU Kun JIANG Bao-qing WEI Qing |
| Institution: | 1. Institute of Data and Knowledge Engineering, Henan University, Kaifeng 475001;The Personnel Department, Zhengzhou Institute of Aeronautical Industry Management,Zhengzhou 450000 2. Institute of Data and Knowledge Engineering, Henan University, Kaifeng 475001 3. The Computer Science Department, Henan University of Finance and Economics, Zhengzhou 450000 |
| Abstract: | The classical algorithm of finding association rules generated by a frequent itemset has to generate all non-empty subsets of the frequent itemset as candidate set of consequents. Xiongfei Li aimed at this and proposed an improved algorithm. The algorithm finds all consequents layer by layer, so it is breadth-first. In this paper, we propose a new algorithm Generate Rules by using Set-Enumeration Tree (GRSET) which uses the structure of Set-Enumeration Tree and depth-first method to find all consequents of the association rules one by one and get all association rules correspond to the consequents. Experiments show GRSET algorithm to be practicable and efficient. |
| Keywords: | association rule frequent itemset breath-first depth-first consequent |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |