A novel association rule mining method for the identification of rare functional dependencies in Complex Technical Infrastructures from alarm data
作者：
Highlights：
• We propose a data-driven method for identifying rare functional dependencies.
• The method is tailored for Complex Technical Infrastructures (CTIs).
• The method is based on a novel association rule mining approach.
• The method reduces the computational effort required to identify rare dependencies.
• The method is validated considering a real dataset from the CTI of CERN.
摘要
•We propose a data-driven method for identifying rare functional dependencies.•The method is tailored for Complex Technical Infrastructures (CTIs).•The method is based on a novel association rule mining approach.•The method reduces the computational effort required to identify rare dependencies.•The method is validated considering a real dataset from the CTI of CERN.
论文关键词：Complex Technical Infrastructures,Rare functional dependencies,Association rules,Alarm data,Abnormal behaviors
论文评审过程：Received 17 April 2020, Revised 31 December 2020, Accepted 31 December 2020, Available online 5 January 2021, Version of Record 18 January 2021.
论文官网地址：https://doi.org/10.1016/j.eswa.2021.114560
