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2005 International Conference on Cyberworlds (CW'05)
Research on Association Rules Mining AlgorithmWith Item Constraints
Singapore
November 23-November 25
ISBN: 0-7695-2378-1
Nan Lu, Shenzhen University, Shenzhen, China
Jing-Zhou Zhou, Shenzhen University, Shenzhen, China
Wang Zhe, Jilin University, Changchun, China
Chun-Guang Zhou, Jilin University, Changchun, China
The issues in the field of association rules mining with specific items are discussed first. To solve the problems in the ordinary algorithm, we put forward a new but efficient mining algorithm with itemconstraints, called EclatII. We then give an analysis on the performance of the algorithm as well as on its strategy. The experimental result shows that the Eclatll algorithm is more robust in items of using "low support" and "long pattern" association rules than others.
Index Terms:
data mining; association rules; item constrains; frequent item-set; lattice theory
Citation:
Nan Lu, Jing-Zhou Zhou, Wang Zhe, Chun-Guang Zhou, "Research on Association Rules Mining AlgorithmWith Item Constraints," cw, pp.325-329, 2005 International Conference on Cyberworlds (CW'05), 2005
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