Frequent itemset mining using cellular learning automata

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• 作者：Mohammad Karim Sohrabi ; ^{Amir_sohraby@aut.ac.ir} ; Reza Roshani ^{r.roshany@gmail.com}
• 关键词：Frequent itemset mining ; Cellular automata ; Data mining ; Association rules ; Parallel frequent itemset mining
• 刊名：Computers in Human Behavior
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：68
• 期：Complete
• 页码：244-253
• 全文大小：1575 K
• 卷排序：68

文摘

In this paper, a frequent itemset mining method is presented. We use cellular learning automata to do fast parallel mining process. The proposed algorithm was tested and the results were compared to SABMA. Experiments are conducted on several experimental data sets with different minsups. Performance study shows that our algorithm outperforms the best former algorithms.