影响因子：5.019
DOI码：10.1007/s10489-021-02407-1
发表刊物：Applied Intelligence
关键字：Fuzzy grid table; Fuzzy temporal association rule; Incremental mining; Item lifespan
摘要：Traditional temporal association rules mining algorithms cannot dynamically update the temporal association rules within the valid time interval with increasing data. In this paper, a new algorithm called incremental fuzzy temporal association rule mining using fuzzy grid table (IFTARMFGT) is proposed by combining the advantages of boolean matrix with incremental mining. First, multivariate time series data are transformed into discrete fuzzy values that contain the time intervals and fuzzy membership. Second, in order to improve the mining efficiency, the concept of boolean matrices was introduced into the fuzzy membership to generate a fuzzy grid table to mine the frequent itemsets. Finally, in view of the Fast UPdate (FUP) algorithm, fuzzy temporal association rules are incrementally mined and updated without repeatedly scanning the original database by considering the lifespan of each item and inheriting the information from previous mining results. The experiments show that our algorithm provides better efficiency and interpretability in mining temporal association rules than other algorithms. © 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
论文类型：期刊论文
学科门类：工学
文献类型：J
卷号：52
期号：2
页面范围：1389 - 1405
ISSN号：0924669X
是否译文：否
发表时间：2022-01-01
收录刊物：SCI
发布期刊链接：https://link.springer.com/article/10.1007/s10489-021-02407-1