Unusual customer response identification and visualization based on text mining and anomaly detection

作者：

Highlights：

• A text analytics framework for understanding unusual customer responses is proposed.

• Significant but rare customer requirements can be automatically identified.

• Unusual responses are identified by machine learning-based anomaly detection method.

• Word and phrase networks for significant keywords are visualized.

摘要

•A text analytics framework for understanding unusual customer responses is proposed.•Significant but rare customer requirements can be automatically identified.•Unusual responses are identified by machine learning-based anomaly detection method.•Word and phrase networks for significant keywords are visualized.

论文关键词：Voice of customers,Keyword network,Local outlier factor,TF-IDF

论文评审过程：Received 27 January 2019, Revised 29 August 2019, Accepted 28 November 2019, Available online 29 November 2019, Version of Record 6 December 2019.

论文官网地址：https://doi.org/10.1016/j.eswa.2019.113111