Minimal infrequent pattern based approach for mining outliers in data streams

作者：

Highlights：

• Minimal Infrequent Pattern based Outlier Detection.

• An algorithm for mining minimal infrequent patterns in data streams.

• Three simple factors deciding outliers.

• An algorithm for detecting outliers based on mined minimal infrequent patterns.

• Experimental results with real time sensor data and publically available UCI data set.

摘要

•Minimal Infrequent Pattern based Outlier Detection.•An algorithm for mining minimal infrequent patterns in data streams.•Three simple factors deciding outliers.•An algorithm for detecting outliers based on mined minimal infrequent patterns.•Experimental results with real time sensor data and publically available UCI data set.

论文关键词：Minimal infrequent pattern,Outlier detection,Data streams,Data mining

论文评审过程：Available online 13 October 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2014.09.053