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- W2387545470 abstract "The research on association rule is an important problem in data mining,how to efficiently discover frequent itemsets is a key problem in association rule research.According to the statistical nature of database transaction,and based on the maximum frequent itemsets discovery algorithm Apriori and its variants,this paper proposes a new algorithm for discovering maximum frequent itemsets that based on layer.Firstly,the algorithm judged the overall frequency of the candidate itemsets,and then through the introduction of the overall strategy,sequencing strategy,the minimum strategy,effectively reduced the comparison times between database transactions and candidates in the process of discovering maximum frequent itemsets.Experimental results show that:when finding maximum frequent itemsets,the efficiency of this algorithm is much better than Apriori in dealing with the task that with large number of database transaction." @default.
- W2387545470 created "2016-06-24" @default.
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- W2387545470 date "2010-01-01" @default.
- W2387545470 modified "2023-09-24" @default.
- W2387545470 title "Algorithm for mining maximal frequent itemsets based on layer" @default.
- W2387545470 hasPublicationYear "2010" @default.
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