Activity discovering and modelling with labelled and unlabelled data in smart environments

作者：

Highlights：

• We propose an activity recognition model balancing accuracy, overhead, data labelling.

• We propose a similarity measurement method to effectively discover activity patterns.

• We perform comprehensive experimental and comparison studies to validate our method.

摘要

•We propose an activity recognition model balancing accuracy, overhead, data labelling.•We propose a similarity measurement method to effectively discover activity patterns.•We perform comprehensive experimental and comparison studies to validate our method.

论文关键词：Data mining,Machine learning,Activity recognition,Similarity measurement,Labelled and unlabelled data,Smart environments

论文评审过程：Available online 11 April 2015.

论文官网地址：https://doi.org/10.1016/j.eswa.2015.04.005