Improved algorithm based on Apriori algorithm
LI Shi-song
Abstract
LI Shi-song
Abstract
Mining association rules is one of the most important topics in data mining. In order to mine association rules quickly, the Apriori algorithm is analyzed, and in this foundation one kind of improved algorithm is proposed which is called NApriori algorithm. In order to mine association rules, it used frequent 1 itemset to reorganize the transaction database. It only needed two times of scanning, and had avoided the tedious connection step and the deletion step of the Apriori algorithm. The experiment indicates that this method has a better performance compared to the Apriori algorithm.
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Mining association rules is one of the most important topics in data mining. In order to mine association rules quickly, the Apriori algorithm is analyzed, and in this foundation one kind of improved algorithm is proposed which is called NApriori algorithm. In order to mine association rules, it used frequent 1 itemset to reorganize the transaction database. It only needed two times of scanning, and had avoided the tedious connection step and the deletion step of the Apriori algorithm. The experiment indicates that this method has a better performance compared to the Apriori algorithm.
Key concepts: Apriori algorithm, Association rule learning, Computer science, Database transaction, Algorithm, Data mining, A priori and a posteriori, GSP Algorithm