| 基于规模约简和多支持度的关联规则挖掘 |
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| 引用本文： | 史原,鲁汉榕,罗菁,高婷.基于规模约简和多支持度的关联规则挖掘[J].计算机工程与设计,2006,27(21):4105-4107,4114. |
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| 作者姓名： | 史原 鲁汉榕 罗菁 高婷 |
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| 作者单位： | 1. 空军雷达学院,研究生管理大队,湖北,武汉,430019
2. 空军雷达学院,信息与指挥自动化系,湖北,武汉,430019 |
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| 摘 要： | 关联规则挖掘的经典算法是Apriori算法，但是存在两大突出的问题，即多次扫描事务数据库和使用单一的支持度，导致了由于事务数据库的规模而增加搜索时间和产生冗余规则或有效规则被丢弃。以往的改进算法只从其中一方面进行考虑。因此同时考虑存在问题，给出了一种基于规模约简和多支持度的关联规则挖掘算法。分析和试验显示在效率上有提高。
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| 关 键 词： | 数据挖掘 关联规则 经典算法 支持度 频繁集 |
| 文章编号： | 1000-7024（2006）21-4105-03 |
| 收稿时间： | 2006-03-15 |
| 修稿时间： | 2006-03-15 |
Mining association rules based on reduced database and multi-support |
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| SHI Yuan,LU Han-rong,LUO Jing,GAO Ting.Mining association rules based on reduced database and multi-support[J].Computer Engineering and Design,2006,27(21):4105-4107,4114. |
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| Authors: | SHI Yuan LU Han-rong LUO Jing GAO Ting |
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| Affiliation: | 1. Department of Graduate Management, Air Force Radar Academy, Wuhan 430019, China; 2. Department of Information and Command Automation, Air Force Radar Academy, Wuhan 430019, China |
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| Abstract: | The classical algorithm for mining association rules is Apriori algorithm. But there are two problems in Apriori algorithm. They are scanning the database for many times and using single-support. Existing optimizing algorithms consider only one of the two problems and hence have their limitations. An algorithm for mining association rules based on reduced database and multi-support is given. Analysis and test show an improvement in efficiency. |
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| Keywords: | data mining association rule classical algorithm support frequent itemset |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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