A novel semi-supervised framework for call center agent malpractice detection via neural feature learning

作者：

Highlights：

• Call center agent malpractice is detectable by means of clustering.

• Optimizing clustering results via neural network-based feature learning.

• The mean duration of silence in agents’ calls is a key performance indicator.

摘要

•Call center agent malpractice is detectable by means of clustering.•Optimizing clustering results via neural network-based feature learning.•The mean duration of silence in agents’ calls is a key performance indicator.

论文关键词：Telemarketing,Semi-supervised learning,Clustering,Automatic malpractice detection,Neural networks,Machine learning

论文评审过程：Received 11 April 2020, Revised 12 July 2022, Accepted 13 July 2022, Available online 20 July 2022, Version of Record 26 July 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118173