There are several mining algorithms of association rules. One of the mostpopular algorithms is Apriori that is used to extract frequent itemsets fromlarge database and getting the association rule for discovering the knowledge.Based on this algorithm, this paper indicates the limitation of the originalApriori algorithm of wasting time for scanning the whole database searching onthe frequent itemsets, and presents an improvement on Apriori by reducing thatwasted time depending on scanning only some transactions. The paper shows byexperimental results with several groups of transactions, and with severalvalues of minimum support that applied on the original Apriori and ourimplemented improved Apriori that our improved Apriori reduces the timeconsumed by 67.38% in comparison with the original Apriori, and makes theApriori algorithm more efficient and less time consuming.
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