期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2015
卷号：5
期号：1
页码：145-147
出版社：International Journal of Soft Computing & Engineering
摘要：To find the frequent item sets from the large big data sets, association rule mining technique of data mining is used. Computer takes too much time to generate all frequent item sets from large big data sets using association rule mining. This can be enhanced, if the time taken to generate association rules is minimized. So here in this work, artificial bee colony (ABC) algorithm with one additional operator, called crossover operator, is used for optimizing the association rules. Due to the better exploration property, crossover operator is used with artificial bee colony algorithm. Experimental results show that the proposed algorithm, for optimizing association rules from big datasets, efficiency is better than the other previously proposed algorithm like KNN and standard ABC algorithm.
