Frequent itemset mining using cellular learning automata
作者：
Highlights：
• 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.
摘要
•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.
论文关键词：Frequent itemset mining,Cellular automata,Data mining,Association rules,Parallel frequent itemset mining
论文评审过程：Received 21 January 2016, Revised 14 October 2016, Accepted 20 November 2016, Available online 26 November 2016, Version of Record 26 November 2016.
论文官网地址：https://doi.org/10.1016/j.chb.2016.11.036
