Efficient Frequent Itemsets Mining by Sampling
Yanchang Zhao, Chengqi Zhang, Shichao Zhang · 2006
Abstract. 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