| 基于SOFM网络的多层模糊关联规则挖掘算法 |
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| 引用本文： | 李学俊,李龙澍,徐怡.基于SOFM网络的多层模糊关联规则挖掘算法[J].华南理工大学学报(自然科学版),2007,35(5):81-85. |
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| 作者姓名： | 李学俊 李龙澍 徐怡 |
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| 作者单位： | 1. 安徽大学,计算智能与信号处理教育部重点实验室,安徽,合肥,230039
2. 安徽大学,计算机科学与技术学院,安徽,合肥,230039 |
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| 基金项目： | 国家自然科学基金资助项目(60273043)，安徽省自然科学基金资助项目(050420204)，安徽省教育厅自然科学研究项目(KJ2007B153) |
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| 摘 要： | 为了表示复杂庞大的概念层次树,文中提出了一种更加通用的编码方案,将概念分层应用于模糊关联规则的挖掘.此外,为解决隶属度函数难以主观确定的问题,引入一种SOFM网络来确定样本数据的隶属度函数.基于改进的概念层次树的编码方案和SOFM网络,将模糊集引入关联规则挖掘中,设计了一种新的多层模糊关联规则挖掘算法.实验结果表明,该算法可以有效地挖掘出易于理解的、有意义的多层次模糊关联规则,具有很好的效率和伸缩性.
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| 关 键 词： | 自组织特征映射网络 概念分层 模糊集 关联规则 |
| 文章编号： | 1000-565X（2007）05-0081-05 |
| 修稿时间： | 2006-11-20 |
Mining Algorithm for Multi-Level Fuzzy Association Rules Based on SOFM Network |
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| Li Xue-jun,Li Long-shu,Xu Yi.Mining Algorithm for Multi-Level Fuzzy Association Rules Based on SOFM Network[J].Journal of South China University of Technology(Natural Science Edition),2007,35(5):81-85. |
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| Authors: | Li Xue-jun Li Long-shu Xu Yi |
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| Abstract: | In order to represent a complex large concept hierarchy tree,this paper proposes a more general coding scheme which applies concept hierarchy into the mining of fuzzy association rules.As it is difficult to determine the membership function subjectively,a self-organizing feature map(SOFM) network is introduced to determine the membership function of sample data.Based on the improved coding scheme and the SOFM network,fuzzy set is then introduced to design a new algorithm of mining multi-level fuzzy association rules.Experimental results show that the proposed algorithm is of high efficiency and scalability and can effectively mine multi-level fuzzy association rules that are meaningful and easily understandable. |
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| Keywords: | self-organizing feature map network concept hierarchy fuzzy set association rule |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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