Activity recognition with weighted frequent patterns mining in smart environments

作者：

Highlights：

• We propose an efficient frequent activity patterns mining in smart environments.

• We build an accurate activity classifier based on the mined frequent patterns.

• We distinguish overlapped activities with global and local weights of sensor events.

• We use publicly available dataset of smart environments to validate our methods.

摘要

•We propose an efficient frequent activity patterns mining in smart environments.•We build an accurate activity classifier based on the mined frequent patterns.•We distinguish overlapped activities with global and local weights of sensor events.•We use publicly available dataset of smart environments to validate our methods.

论文关键词：Data mining,Association rule,Activity recognition,Global and local weight,Smart environments

论文评审过程：Available online 30 April 2015, Version of Record 15 May 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.04.020