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AMT
2006
Springer

Efficient Frequent Itemsets Mining by Sampling

13 years 9 months ago
Efficient Frequent Itemsets Mining by Sampling
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
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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