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Improved Association Rule Mining by Modified Trimming  

Hwang, Won-Tae (School of Electrical and Electronics Engineering, Chung-Ang University)
Kim, Dong-Seung (School of Electrical Engineering, Korea University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.45, no.3, 2008 , pp. 15-21 More about this Journal
Abstract
This paper presents a new association mining algorithm that uses two phase sampling for shortening the execution time at the cost of precision of the mining result. Previous FAST(Finding Association by Sampling Technique) algorithm has the weakness in that it only considered the frequent 1-itemsets in trimming/growing, thus, it did not have ways of considering mulit-itemsets including 2-itemsets. The new algorithm reflects the multi-itemsets in sampling transactions. It improves the mining results by adjusting the counts of both missing itemsets and false itemsets. Experimentally, on a representative synthetic database, the algorithm produces a sampled subset of results with an increased accuracy in terms of the 2-itemsets while it maintains the same 1uality of the data set.
Keywords
data mining; association rule mining; random sampling;
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