| 关联规则挖掘研究 |
| |
| 引用本文： | 张云洋,袁源. 关联规则挖掘研究[J]. 计算机时代, 2009, 0(7): 6-8 |
| |
| 作者姓名： | 张云洋 袁源 |
| |
| 作者单位： | 西藏大学图书馆,西藏,拉萨,850012;西藏大学现代教育技术中心 |
| |
| 摘 要： | 关联规则挖掘是一种重要的数据挖掘技术,缘自"啤酒与尿布"问题出现这项技术以来,已有许多学者提出了多种关联规则挖掘算法。这些关联规则挖掘算法主要分为以Apriori为代表的"产生-测试"范型和以FP-growth为代表的采用复杂数据结构压缩存储空间的范型。文章将这两种代表算法进行了对比分析。
|
| 关 键 词： | 数据挖掘 关联规则 数据库 支持度 可信度 |
Study of Association Rule Mining |
| |
| ZHANG Yun-yang,YUAN Yuan. Study of Association Rule Mining[J]. Computer Era, 2009, 0(7): 6-8 |
| |
| Authors: | ZHANG Yun-yang YUAN Yuan |
| |
| Affiliation: | 1.Tibet University Library;Lasa 850012;China;2.Modern Education Technology Center;Tibet University |
| |
| Abstract: | Association rule mining is an important technique for data mining.Since being brought up by case of "beer and napkin",many scholars have proposed several kinds of association rule mining algorithms.These algorithms mainly belong to two basic patterns.One is "construct-test" pattern which is represented by Apriori,the other is represented by FP-growth that employs complicated data structure to compress memory space.The two representative algorithms are compared and analyzed in the article. |
| |
| Keywords: | data mining association rule database support confidence |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
