Feature engineering vs. deep learning for paper section identification: Toward applications in Chinese medical literature
作者：
Highlights：
• Our identified effective features and proposed effective model SLSTM extend section identification issue to Chinese traditional medical paper.
• The dependencies between sentences and the structure of articles are an important aspect to deal with the section identification problem.
• Our model has a potential to be used to address other sentence classification problems.
摘要
•Our identified effective features and proposed effective model SLSTM extend section identification issue to Chinese traditional medical paper.•The dependencies between sentences and the structure of articles are an important aspect to deal with the section identification problem.•Our model has a potential to be used to address other sentence classification problems.
论文关键词：Section identification,Feature engineering,Deep learning,Chinese medicinal literature
论文评审过程：Received 20 April 2019, Revised 7 December 2019, Accepted 13 January 2020, Available online 31 January 2020, Version of Record 31 January 2020.
论文官网地址：https://doi.org/10.1016/j.ipm.2020.102206
