Accelerated Frequent Closed Sequential Pattern Mining for uncertain data

作者：

Highlights：

• Compared with basic PFCSM-FF, PFCSM-CF enhances the efficiency by avoiding invalid computation.

• A PFCSM-CC algorithm is implied to reduces the computational cost of frequent closed probability.

• The experiments are conducted to evaluate the performance of PFCSM-CF and PFCSM-CC.

摘要

•Compared with basic PFCSM-FF, PFCSM-CF enhances the efficiency by avoiding invalid computation.•A PFCSM-CC algorithm is implied to reduces the computational cost of frequent closed probability.•The experiments are conducted to evaluate the performance of PFCSM-CF and PFCSM-CC.

论文关键词：Uncertain database,Frequent closed sequences,Possible world semantics

论文评审过程：Received 31 May 2021, Revised 22 March 2022, Accepted 13 April 2022, Available online 27 April 2022, Version of Record 20 May 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.117254