| 基于事务标识列表的关联规则挖掘算法 |
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| 引用本文： | 王强.基于事务标识列表的关联规则挖掘算法[J].现代图书情报技术,2008,3(8):63-69. |
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| 作者姓名： | 王强 |
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| 作者单位： | 中国科学院国家科学图书馆,北京,100190;中国科学院研究生院,北京,100049 |
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| 摘 要： | 设计并采用Java语言实现基于事务数据库标识列表的频繁项集的产生算法——TidlistApriori。通过与采用Hash-Tree的Apriori算法进行比较，表明TidlistApriori能够提高频繁项集的产生效率，可以成为主题关联挖掘的有效算法工具。
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| 关 键 词： | 频繁项集 关联规则挖掘 数据挖掘 主题关联 |
| 收稿时间： | 2008-05-09 |
| 修稿时间： | 2008-06-12 |
Algorithm for Mining Association Rule Based on the Identifier Lists of Transactions |
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| Wang Qiang.Algorithm for Mining Association Rule Based on the Identifier Lists of Transactions[J].New Technology of Library and Information Service,2008,3(8):63-69. |
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| Authors: | Wang Qiang |
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| Institution: | 1(National Science Library, Chinese Academy of Sciences, Beijing 100190, China)
2(Graduate University of the Chinese Academy of Sciences, Beijing 100049, China) |
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| Abstract: | This paper designs and implements an algorithm named TidlistApriori for mining association rule based on the identifier lists of transactions in database using Java.The results of experiment comparing TidlistApriori with Apriori based on Hash-Tree indicate that this algorithm can improve the efficiency of finding frequent item sets,and TidlistApriori can be used as efficient tool for mining topic association. |
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| Keywords: | Frequent item sets Association rule mining Data mining Topic association |
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