Extractive multi-document text summarization using a multi-objective artificial bee colony optimization approach
作者：
Highlights：
• An approach to extractive multi-document text summarization is proposed.
• Content coverage and redundancy reduction objectives are optimized.
• This computer-based approach is tested with Document Understanding Conference dataset.
• It can be applied in any document collection of a specific topic.
• It improves the existing average results in the scientific literature.
摘要
•An approach to extractive multi-document text summarization is proposed.•Content coverage and redundancy reduction objectives are optimized.•This computer-based approach is tested with Document Understanding Conference dataset.•It can be applied in any document collection of a specific topic.•It improves the existing average results in the scientific literature.
论文关键词：Artificial bee colony,Content coverage,Multi-document summarization,Multi-objective optimization,Redundancy reduction
论文评审过程：Received 18 July 2017, Revised 20 November 2017, Accepted 22 November 2017, Available online 23 November 2017, Version of Record 10 September 2018.
论文官网地址：https://doi.org/10.1016/j.knosys.2017.11.029
