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In recent years, the amount of data into a geometric growth puts forward higher requirements on data mining algorithm. In the process of frequent itemsets of traditional Apriori algorithm produced, frequent itemsets' generation and storage are quite a waste of time and space. In this paper, we put forward a new Hash table and use the technology to improve the algorithm and get SamplingHT algorithm, through a lot of contrast experiments showed that the new algorithm enhances performance when frequent itemset is generated, and effectively reduce the database scan times, In order to achieve more optima. |
