[1] Lu Jianjiang, , Xu Baowen, et al. Classification methods of association rules with linguistic terms [J]. Journal of Southeast University (English Edition), 2004, 20 (1): 21-25. [doi:10.3969/j.issn.1003-7985.2004.01.005]

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Classification methods of association rules with linguistic terms()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

20

Issue:

2004 1

Page:

21-25

Research Field:

Computer Science and Engineering

Publishing date:

2004-03-30

Info

Title:

Classification methods of association rules with linguistic terms

Author(s):

Lu Jianjiang¹;  2;  3;  Xu Baowen¹;  3;  Kang Dazhou¹;  3

¹Department of Computer Science and Engineering, Southeast University, Nanjing 210096, China
²Institute of Science, PLA University of Science and Technology, Nanjing 210007, China
³Jiangsu Institute of Software Quality, Nanjing 210096, China

Keywords:

data mining;  linguistic terms;  association rules;  classification

PACS:

TP311.13

DOI:

10.3969/j.issn.1003-7985.2004.01.005

Abstract:

A partition of intervals method is adopted in current classification based on associations(CBA), but this method cannot reflect the actual distribution of data and still the problem of sharp boundary exists. In this paper, the classification system based on the longest association rules with linguistic terms is first discussed, and the shortcoming of this classification system is analyzed. Then, the classification system based on the short association rules with linguistic terms is presented. The example shows that the accuracy of the classification system based on the association rules with linguistic terms is better than two popular classification methods: C4.5 and CBA.

References:

[1] Quinlan J R. C4.5: programs for machine learning [M]. San Mateo, CA: Morgan Kaufmann, 1993. 28-38.
[2] Agrawal R, Imieliski T, Swami A. Mining association rules between sets of items in large databases[A]. In: Proceedings of ACM SIGMOD Conference on Management of Data [C]. Washington DC, 1993. 207-216.
[3] Agrawal R, Srikant R. Fast algorithms for mining association rules [A]. In: Proceedings of the International Conference on Very Large Databases [C]. Santiago, Chile, 1994. 487-499.
[4] Park J S, Chen M S, Yu P S. An effective hash-based algorithm for mining association rules [A]. In: Proceedings of the 1995 ACM-SIGMOD International Conference on Management of Data [C]. San Jose, CA, 1995. 175-186.
[5] Srikant R, Agrawal R. Mining quantitative association rules in large relational tables [A]. In: Proceedings of the ACM-SIGMOD Conference on Management of Data [C]. Montreal, Canada, 1996. 1-12.
[6] Liu B, Hsu W, Ma Y. Integrating classification and association rule mining [A]. In: Proceedings of the International Conference on Knowledge Discovery and Data Mining[C]. New York, 1998. 80-86.
[7] Chan M K, Ada F, Man H W. Mining fuzzy association rules in database [A]. In: Proceedings of the ACM Sixth International Conference on Information and Knowledge Management [C]. Las Vegas, Neveda, 1997.10-14.
[8] Lu Jianjiang, Qian Zuoping, Song Ziling. Application of normal cloud association rules on prediction[J]. Journal of Computer Research and Development, 2000, 37(11): 1317-1320.(in Chinese)
[9] Lu Jianjiang, Qian Zuoping, Song Ziling. Mining linguistic valued association rules [J]. Journal of Software, 2001, 12(4): 607-611.(in Chinese)
[10] Zou Xiaofeng, Lu Jianjiang, Song Ziling. Mining linguistic valued association rules[J]. Journal of System Simulation, 2002, 14(9): 1130-1132.(in Chinese)
[11] Lu Jianjiang. Research on algorithms of mining association rules with weighted items [J]. Journal of Computer Research and Development, 2002, 39(10): 1281-1286.(in Chinese)
[12] Hathaway R J, Davenport J W, Bezdek J C. Relational dual of the c-means algorithms [J]. Pattern Recognition, 1989, 22(2): 205-212.

Memo

Memo:

Biography: Lu Jianjiang(1968—), male, doctor, associate professor, jjlu@seu.edu.cn.

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