[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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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

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

Keywords:

ontology;  association rules mining;  semantic relativity

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.

References:

[1] Xie Hongwei, Yu Xueli, Li Juanli, et al.Study on ontology-based a priori algorithm applying to emergency decision system[C]//Proceedings of Fuzzy Systems and Knowledge Discovery.Nevada, USA, 2007:669-673.
[2] Cešpivová H, Rauch J, Svátek V, et al.Roles of medical ontology in association mining CRISP-DM cycle[C]//Proceedings of Knowledge Discovery and Ontologies at 15th European Conference on Machine Learning/8th European Conference on Principles and Practice of Knowledge Discovery in Databases.Pisa, Italy, 2004:217-229.
[3] Kuo Yen-Ting, Lonie Andrew, Sonenberg Liz, et al.Domain ontology driven data mining:a medical case study[C]//Proceedings of the 2007 International Workshop on Domain Driven Data Mining.San Jose, CA, USA, 2007:11-17.
[4] Farzanyar Zahra, Kangavari Moharnrnadreza, Hashemi Sattar.A new algorithm for mining fuzzy association rules in the large databases based on ontology[C]//Proc of Sixth IEEE International Conference on Data Mining-Workshops(ICDMW’OG).Hong Kong, China, 2006:65-69.
[5] Wu Chin-Ang, Lin Wen-Yang, Wu Chuan-Chun.Ontology-assisted query formulation in multidimensional association rules mining[C]//Proceedings of 2007 IEEE International Conference on Granular Computing. Washington, DC, USA:IEEE Computer Society, 2007:358-361.
[6] Tseng Ming-Cheng, Lin Wen-Yang, Jeng Rong.Incremental maintenance of ontology-exploiting association rules[C]//Proc of 2007 International Conference on Machine Learning and Cybernetics. Hong Kong, China, 2007:2280-2285.
[7] Won Dongwoo, McLeod Dennis.Ontology-driven rules generalization and categorization for market data[C]//Proceedings of the 23rd ICDE Workshops on Data Mining and Business Intelligence.Istanbul, Turkey, 2007:917-923.
[8] Li Y, Bandar Z A, Mclean D.An approach for measuring semantic similarity between words using multiple information sources[J].IEEE Trans on Knowledge and Data Engineering, 2003, 15(4):871-882.
[9] Lord P W, Stevens R D.Investigating semantic similarity measures across the gene ontology:the relationship between sequence and annotation[J].Bioinformatics, 2003, 19(10):1275-1283.
[10] Rodríguze M Andrea, Egenhofer Max J.Determining semantic similarity among entity classes from different ontologies[J].IEEE Trans on Knowledge and Data Engineering, 2003, 15(2):442-456.

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.

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