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[1] Zhang Lei, Xia Shixiong, Zhou Yong, Xia Zhanguo, et al. Study on association rules mining based on semantic relativity [J]. Journal of Southeast University (English Edition), 2008, 24 (3): 358-360. [doi:10.3969/j.issn.1003-7985.2008.03.026]
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Study on association rules mining based on semantic relativity()
基于语义相关性的关联规则挖掘研究
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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:
24
Issue:
2008 3
Page:
358-360
Research Field:
Computer Science and Engineering
Publishing date:
2008-09-30

Info

Title:
Study on association rules mining based on semantic relativity
基于语义相关性的关联规则挖掘研究
Author(s):
Zhang Lei Xia Shixiong Zhou Yong Xia Zhanguo
School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China
张磊 夏士雄 周勇 夏战国
中国矿业大学计算机科学与技术学院, 徐州 221116
Keywords:
ontology association rules mining semantic relativity
本体 关联规则挖掘 语义相关性
PACS:
TP311.5
DOI:
10.3969/j.issn.1003-7985.2008.03.026
Abstract:
An association rules mining method based on semantic relativity is proposed to solve the problem that there are more candidate item sets and higher time complexity in traditional association rules mining.Semantic relativity of ontology concepts is used to describe complicated relationships of domains in the method.Candidate item sets with less semantic relativity are filtered to reduce the number of candidate item sets in association rules mining.An ontology hierarchy relationship is regarded as a directed acyclic graph rather than a hierarchy tree in the semantic relativity computation.Not only direct hierarchy relationships, but also non-direct hierarchy relationships and other typical semantic relationships are taken into account.Experimental results show that the proposed method can reduce the number of candidate item sets effectively and improve the efficiency of association rules mining.
为了解决传统关联规则挖掘中候选集数量过多, 计算时间复杂度过高的问题, 提出了基于语义相关性的关联规则挖掘方法.该方法采用本体概念之间的语义相关性描述领域中的复杂关系, 通过语义相关度过滤掉领域中相关性较小的候选集, 以减少关联规则挖掘中候选集的数量.计算语义相关性时, 将本体层次关系看作有向无环图而不是层次树, 不仅考虑直接层次关系, 还考虑非直接层次关系和其他典型语义关系.实验结果表明, 该方法能有效减少候选集数量, 提高关联规则挖掘的效率.

References:

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Memo

Memo:
Biographies: Zhang Lei(1977—), male, doctor, lecturer, zhanglei-zyx@163.com;Xia Shixiong(1961—), male, professor, xiasx@cumt.edu.cn.
Foundation items: The National Natural Science Foundation of China(No.50674086), Specialized Research Fund for the Doctoral Program of Higher Education(No.20060290508), the Science and Technology Fund of China University of Mining and Technology(No.2007B016).
Citation: Zhang Lei, Xia Shixiong, Zhou Yong, et al.Study on association rules mining based on semantic relativity[J].Journal of Southeast University(English Edition), 2008, 24(3):358-360.
Last Update: 2008-09-20