Impact Factor:  5.019

DOI number:  10.1007/s10489-021-02407-1

Journal:  Applied Intelligence

Key Words:  Fuzzy grid table; Fuzzy temporal association rule; Incremental mining; Item lifespan

Abstract:  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.

Indexed by:  Journal paper

Discipline:  Engineering

Document Type:  J

Volume:  52

Issue:  2

Page Number:  1389 - 1405

ISSN No.:  0924669X

Translation or Not:  no

Date of Publication:  2022-01-01

Included Journals:  SCI

Links to published journals:  https://link.springer.com/article/10.1007/s10489-021-02407-1