C3Ro: An efficient mining algorithm of extended-closed contiguous robust sequential patterns in noisy data
作者：
Highlights：
• New notion of apprehensibility to represent the quality of pattern mining output.
• Two constraints to improve apprehensibility and noise-resistance of pattern mining.
• A generic, highly parameterizable and efficient pattern mining algorithm.
• Experimentations on various datasets to evaluate the algorithm and both constraints.
摘要
•New notion of apprehensibility to represent the quality of pattern mining output.•Two constraints to improve apprehensibility and noise-resistance of pattern mining.•A generic, highly parameterizable and efficient pattern mining algorithm.•Experimentations on various datasets to evaluate the algorithm and both constraints.
论文关键词：Data mining,Sequential pattern mining,Closed contiguous pattern,Noisy data,Constraints,Efficiency
论文评审过程：Received 4 December 2018, Revised 28 March 2019, Accepted 24 April 2019, Available online 25 April 2019, Version of Record 2 May 2019.
论文官网地址：https://doi.org/10.1016/j.eswa.2019.04.058
