Catering for unique tastes: Targeting grey-sheep users recommender systems through one-class machine learning

作者：

Highlights：

• Intelligent recommendations targeting grey sheep users with atypical preferences.

• Combining one class learning, outlier detection and cluster analysis.

• Highly accurate recommendations both for regular and grey-sheep users.

• A novel benchmark for future grey-sheep studies.

摘要

•Intelligent recommendations targeting grey sheep users with atypical preferences.•Combining one class learning, outlier detection and cluster analysis.•Highly accurate recommendations both for regular and grey-sheep users.•A novel benchmark for future grey-sheep studies.

论文关键词：Recommender systems,Model-based systems,Machine learning,Grey-sheep,One-class classification

论文评审过程：Received 8 June 2020, Revised 24 September 2020, Accepted 24 September 2020, Available online 29 September 2020, Version of Record 9 October 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.114061