ML Anthology

Abstractive Summarization: A Survey of the State of the Art

Hui Lin, Vincent Ng
AAAI 2019 pp. 9815-9822
doi:10.1609/AAAI.V33I01.33019815 /aaai/2019/lin2019aaai-abstractive/

Abstract

The focus of automatic text summarization research has exhibited a gradual shift from extractive methods to abstractive methods in recent years, owing in part to advances in neural methods. Originally developed for machine translation, neural methods provide a viable framework for obtaining an abstract representation of the meaning of an input text and generating informative, fluent, and human-like summaries. This paper surveys existing approaches to abstractive summarization, focusing on the recently developed neural approaches.

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Text

Lin and Ng. "Abstractive Summarization: A Survey of the State of the Art." AAAI Conference on Artificial Intelligence, 2019. doi:10.1609/AAAI.V33I01.33019815

Markdown

[Lin and Ng. "Abstractive Summarization: A Survey of the State of the Art." AAAI Conference on Artificial Intelligence, 2019.](https://mlanthology.org/aaai/2019/lin2019aaai-abstractive/) doi:10.1609/AAAI.V33I01.33019815

BibTeX

@inproceedings{lin2019aaai-abstractive,
  title     = {{Abstractive Summarization: A Survey of the State of the Art}},
  author    = {Lin, Hui and Ng, Vincent},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2019},
  pages     = {9815-9822},
  doi       = {10.1609/AAAI.V33I01.33019815},
  url       = {https://mlanthology.org/aaai/2019/lin2019aaai-abstractive/}
}