CPM: A general feature dependency pattern mining framework for contrast multivariate time series

作者：

Highlights：

• Unsupervised framework to mine contrast patterns in controlled experiment.

• Customizable regularization techniques.

• Efficient optimization algorithm easily adapt to various models under the framework.

• Highly interpretable results in real world controlled experiments.

摘要

•Unsupervised framework to mine contrast patterns in controlled experiment.•Customizable regularization techniques.•Efficient optimization algorithm easily adapt to various models under the framework.•Highly interpretable results in real world controlled experiments.

论文关键词：Contrast pattern,Feature dependency,Controlled experiment,Driving behavior,Multivariate time series

论文评审过程：Received 18 October 2019, Revised 12 October 2020, Accepted 21 October 2020, Available online 21 October 2020, Version of Record 30 January 2021.

论文官网地址：https://doi.org/10.1016/j.patcog.2020.107711