Extractive single-document summarization based on genetic operators and guided local search

作者：

Highlights：

• A new method for extractive single-document summarization is proposed.

• The new method is based on genetic operators and guided local search.

• Fitness function is based on individual statistical features of each sentence.

• Fitness function also is based on group features of similarity between sentences.

• Proposed method outperforms the state of the art methods.

摘要

•A new method for extractive single-document summarization is proposed.•The new method is based on genetic operators and guided local search.•Fitness function is based on individual statistical features of each sentence.•Fitness function also is based on group features of similarity between sentences.•Proposed method outperforms the state of the art methods.

论文关键词：Extractive summarization,Single document,Memetic algorithm,Guided local search

论文评审过程：Available online 4 January 2014.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.12.042