Efficient mining of extraordinary patterns by pruning and predicting

作者：

Highlights：

• Extraordinary patterns are those with supports and utilities in opposite extremes.

• Estimating tight lower bounds both on supports and utilities are possible.

• Both upper bounds and lower bounds based pruning are effective.

• Pattern growth with pruning and predicting improve efficiency 2 orders of magnitude.

摘要

•Extraordinary patterns are those with supports and utilities in opposite extremes.•Estimating tight lower bounds both on supports and utilities are possible.•Both upper bounds and lower bounds based pruning are effective.•Pattern growth with pruning and predicting improve efficiency 2 orders of magnitude.

论文关键词：Data mining,Pattern mining,Frequent patterns,High utility patterns,Extraordinary patterns

论文评审过程：Received 2 May 2018, Revised 9 January 2019, Accepted 30 January 2019, Available online 31 January 2019, Version of Record 5 February 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.01.079