Association rule mining with mostly associated sequential patterns
作者：
Highlights：
• Extraction of interesting patterns from data in the form of mostly associated sequential patterns.
• Speeding up the finding interesting patterns in data.
• Providing a tool for visual exploration of patterns extracted from data.
• Ability to be used for searching patterns in big data.
• The proposed algorithm can be extended to find different type of patterns such as the weakest associated patterns.
摘要
•Extraction of interesting patterns from data in the form of mostly associated sequential patterns.•Speeding up the finding interesting patterns in data.•Providing a tool for visual exploration of patterns extracted from data.•Ability to be used for searching patterns in big data.•The proposed algorithm can be extended to find different type of patterns such as the weakest associated patterns.
论文关键词：Association rule mining,Interesting rules,Pattern recognition,Big data,Knowledge discovery,Data mining
论文评审过程：Available online 10 November 2014.
论文官网地址：https://doi.org/10.1016/j.eswa.2014.10.049
