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It is an important task in data mining to maintain discovered frequent itemsets for association rule mining. Because most time-consuming operation for mining association rules is to find the frequent ...itemsets from the transaction database. And the database is always updated. However, the algorithms proposed so far for the maintenance of discovered frequent itemsets can only perform with a minimum support threshold which is the same as that of previous mining. If the new result derived with such minimum support is unsatisfactory to a user, the maintaining process may fail. In this paper we propose a new algorithm to maintain discovered frequent itemsets. Our algorithm allows users to adjust the minimum support of maintaining process. And it can be performed repeatedly with a different minimum support until the satisfying results are obtained. We prove the efficiency of our algorithm by experiments with several synthetic transaction databases.続きを見る
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