Using association rules to discover color-emotion relationships based on social tagging
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part I
An efficient approach for generating frequent patterns without candidate generation
Proceedings of the International Conference on Advances in Computing, Communications and Informatics
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Through the study of Apriori algorithm we discover two aspects that affect the efficiency of the algorithm. One is the frequent scanning database, the other is large scale of the candidate itemsets. Therefore, IApriori algorithm is proposed that can reduce the times of scanning database, optimize the join procedure of frequent itemsets generated in order to reduce the size of the candidate itemsets. The results show that the algorithm is better than Apriori algorithm.