影响因子：8.263
DOI码：10.1016/j.asoc.2017.09.013
发表刊物：Applied Soft Computing Journal
关键字：Frequent itemsets tree; Interpretability; Temporal association rule; Temporal relationship
摘要：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.
论文类型：期刊论文
学科门类：工学
文献类型：J
卷号：62
页面范围：817 - 829
ISSN号：15684946
是否译文：否
发表时间：2018-01-01
收录刊物：SCI
发布期刊链接：https://www.sciencedirect.com/science/article/pii/S1568494617305525