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37

AMT
2006
Springer

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Efficient Frequent Itemsets Mining by Sampling

14 years 25 days ago

Efficient Frequent Itemsets Mining by Sampling

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As the first stage for discovering association rules, frequent itemsets mining is an important challenging task for large databases. Sampling provides an efficient way to get approximating answers in much shorter time. Based on the characteristics of frequent itemsets counting, a new bound for sampling is proposed, with which less samples are necessary to achieve the required accuracy and the efficiency is much improved over traditional Chernoff bounds. Keywords. Frequent itemset, sampling

Yanchang Zhao, Chengqi Zhang, Shichao Zhang

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Added	13 Oct 2010
Updated	13 Oct 2010
Type	Conference
Year	2006
Where	AMT
Authors	Yanchang Zhao, Chengqi Zhang, Shichao Zhang

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