Applying the maximum utility measure in high utility sequential pattern mining
作者：
Highlights：
• We introduce a new research work, high utility sequential pattern mining with the maximum utility measure.
• We propose a projection-based PHUS approach for mining this kind of patterns.
• An effective upper-bound model is proposed to reduce search space in the mining process.
• The derived patterns are expected to be more reliable in terms of business.
• Experimental results show that the PHUS is effective in terms of efficiency and scalability.
摘要
•We introduce a new research work, high utility sequential pattern mining with the maximum utility measure.•We propose a projection-based PHUS approach for mining this kind of patterns.•An effective upper-bound model is proposed to reduce search space in the mining process.•The derived patterns are expected to be more reliable in terms of business.•Experimental results show that the PHUS is effective in terms of efficiency and scalability.
论文关键词：Data mining,High utility sequential pattern mining,Sequence utility,Upper bound,Projection
论文评审过程：Available online 25 February 2014.
论文官网地址：https://doi.org/10.1016/j.eswa.2014.02.022
