Extractive multi-document summarization using population-based multicriteria optimization

作者：

Highlights：

• A system with feature extraction and multicriteria optimization technique.

• Uses objective functions that cover both statistical and semantic aspects.

• Population based approach with random weights for features in each generation.

• High Precision and Recall values compared to the other popular methods.

摘要

•A system with feature extraction and multicriteria optimization technique.•Uses objective functions that cover both statistical and semantic aspects.•Population based approach with random weights for features in each generation.•High Precision and Recall values compared to the other popular methods.

论文关键词：Multi-document summarization,Multicriteria optimization,Latent semantic analysis,Non negative matrix factorization,DUC,ROUGE

论文评审过程：Received 9 November 2015, Revised 28 May 2017, Accepted 29 May 2017, Available online 30 May 2017, Version of Record 13 June 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.05.075