CAVIAR: Context-driven Active and Incremental Activity Recognition

作者：

Highlights：

• We propose a novel context-aware and semi-supervised activity recognition method.

• Results show that context reasoning improves semi-supervised activity recognition.

• We show that knowledge-based reasoning outperforms purely data-driven approaches.

摘要

•We propose a novel context-aware and semi-supervised activity recognition method.•Results show that context reasoning improves semi-supervised activity recognition.•We show that knowledge-based reasoning outperforms purely data-driven approaches.

论文关键词：Activity recognition,Mobile computing,Semi-supervised learning,Context-awareness,Hybrid reasoning

论文评审过程：Received 14 November 2019, Revised 21 February 2020, Accepted 23 March 2020, Available online 27 March 2020, Version of Record 16 April 2020.

论文官网地址：https://doi.org/10.1016/j.knosys.2020.105816