Mining temporal association rules with frequent itemsets tree

作者：Wang, Ling^*; Meng, Jianyao; Xu, Peipei; Peng, Kaixiang

来源：Applied Soft Computing, 2018, 62: 817-829.

DOI：10.1016/j.asoc.2017.09.013

• Temporal relationship
• Frequent itemsets tree
• Temporal association rule
• Interpretability

A novel framework for mining temporal association rules by discovering itemsets with frequent itemsets tree is introduced. In order to solve the problem of handling time series by including temporal relation between the multi items into association rules, a frequent itemsets tree is constructed in parallel with mining frequent itemsets to improve the efficiency and interpretability of rule mining without generating candidate itemsets. Experimental results show that our algorithm can provide better efficiency and interpretability in mining temporal association rules in comparison with other algorithms and has good application prospects.

• 出版日期2018-1
• 单位北京科技大学