Extracting highlights of scientific articles: A supervised summarization approach

作者：

Highlights：

• An approach to extracting highlights of scientific articles is proposed.

• The approach is extractive and based on supervised regression models.

• The experiments were conducted on a benchmark collection of articles.

• The proposed approach performed better than classification and summarization methods.

摘要

•An approach to extracting highlights of scientific articles is proposed.•The approach is extractive and based on supervised regression models.•The experiments were conducted on a benchmark collection of articles.•The proposed approach performed better than classification and summarization methods.

论文关键词：Highlight extraction,Extractive summarization,Regression models,Text mining and analytics

论文评审过程：Received 25 August 2019, Revised 21 January 2020, Accepted 12 June 2020, Available online 27 June 2020, Version of Record 7 July 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113659