Abstractive Summarization: A Survey of the State of the Art

Abstrative Summarization: A Survey of the State of the Art

Hui Lin and Vincent Ng.
Proceedings of the 33rd AAAI Conference on Artificial Intelligence, pp. 9815-9822, 2019.

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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.

BibTeX entry

@InProceedings{Lin+Ng:19a,
  author = {Hui Lin and Vincent Ng},
  title = {Abstractive Summarization: A Survey of the State of the Art},
  booktitle = {Proceedings of the 33rd AAAI Conference on Artificial Intelligence},
  pages = {9815--9822},
  year = 2019}