| 基于概念分层关联规则挖掘的研究 |
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| 引用本文： | 王现君,高莉.基于概念分层关联规则挖掘的研究[J].河南科学,2007,25(6):988-991. |
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| 作者姓名： | 王现君 高莉 |
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| 作者单位： | 1. 河南大学,计算机与信息工程学院,河南,开封,475004;河南大学,数据与知识工程研究所,河南,开封,475004
2. 信息工程大学,郑州,450004 |
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| 基金项目： | 河南省高校杰出科研创新人才工程项目 |
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| 摘 要： | 通过加权平均算法(ML_TWA)发现多层关联规则.该算法针对现有多层关联规则挖掘中存在阈值定义不合理的情况,依据多层数据的特点,提出了一种加权平均阈值估计方法,来提高挖掘效率和结果的准确性.实验结果证明这种算法是有效的.
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| 关 键 词： | 概念分层 关联规则 加权平均 数据挖掘 |
| 文章编号： | 1004-3918（2007）06-0988-04 |
| 修稿时间： | 2007-07-08 |
Research on Mining Association Rules Based on Concept Hierarchies |
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| WANG Xian-jun,GAO Li.Research on Mining Association Rules Based on Concept Hierarchies[J].Henan Science,2007,25(6):988-991. |
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| Authors: | WANG Xian-jun GAO Li |
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| Institution: | 1. Sehool of Computer and Information Engineering, Henan University, Kaifeng 475004, China; 2. Institute of Data and Knowledge Engineering, Henan University, Kaifeng 475004, China; 3. Information Engineering University, Zhengzhou 450004, China |
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| Abstract: | Association rules mining is one of the important research fields in data mining.In this paper we present a weighted average method named ML_TWA to discovery multi-level association rules.It put forward a heuristic user-defined method which based on the characteristic of multi-level data to overcome the drawbacks caused by the unreasonable method of defining threshold.So the precision and efficiency of mining association rules is improved,The experimental results show that the efficiency of the algorithm for large databases. |
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| Keywords: | concept hierarchies association rule weighted average data mining |
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